大学生网络利他行为：量表编制与多层线性分析
|
摘要
网络利他行为是指人们在网络环境中表现出来的有利于他人和社会、且不期望得到任何回报的自觉自愿行为。大学生是网络使用最为集中的群体,网络已成为大学生学习和生活不可缺少的工具。大学生的网络利他行为非常普遍,但学者对大学生网络利他行为的研究非常少,更缺乏大学生网络利他行为的测评工具。因此,研究大学生网络利他行为,关注网络给大学生带来的积极影响,既丰富了网络心理学的研究内容,又有利于网络健康文明氛围的营造和大学生人际关系的和谐发展,并为大学生的网络道德教育提供参考。
本文在构建大学生网络利他行为的理论框架、探讨大学生网络利他行为的心理结构模型的基础上,编制了较高质量的大学生网络利他行为量表,并以此量表为工具对大学生网络利他行为的影响因素进行了实证研究。因此,本文主要有两大研究任务。一个任务是编制大学生网络利他行为量表。为确保量表的高质量,本文采用了经典测量理论(CTT)、概化理论(GT)、项目功能差异分析(DIF)、结构方程模型(SEM)等多种心理测量理论和技术相整合的方法。另一任务是探讨影响大学生网络利他行为的个体变量、班级变量和学校变量因素。由于数据存在嵌套关系,本文采用了多层线性分析技术,分别探讨了班级变量和学校变量对大学生网络利他行为及其与网络行为偏好间关系的影响。具体研究结果概述如下：
(1)经典测量理论的研究结果表明：大学生网络利他行为量表(IABSU)包含30个项目,共有4个因子,分别将其命名为网络支持、网络指导、网络分享和网络提醒。
(2)项目功能差异分析结果表明：IABSU不存在性别DIF,但有4个项目存在地域DIF,删除这4个项目后,量表保留26个项目。
(3)概化理论分析结果表明：IABSU取4个维度是较合适的,既能保证较高的测量精度,又有较好的测量效益；IABSU各维度项目数量的设定比较合适；IABSU的4个维度及其整体的测量精度都很高,既可用于常模参照测验,也可用于标准参照测验。
(4)信效度的检验结果表明：IABSU的信度、效度很好,可以作为大学生网络利他行为的有效测评工具。
(5)验证性因素分析和交互效度检验结果表明：大学生网络利他行为是一个多层次多维度的结构,它是一个二阶单因素一阶4因素的结构模型。
(6)班级变量对大学生网络利他行为影响的多层线性分析结果表明：游戏偏好对网络利他行为总分、网络支持和网络分享的影响、交往偏好对网络支持的影响、信息偏好对网络提醒的影响均存在显著的班级差异；班级女生率和班级平均自尊水平对网络支持的班级均值差异有显著的预测作用,女生率或平均自尊水平越高的班级,网络支持的班级平均分数就越高。班级平均每周上网时间和班级平均自尊水平对交往偏好与网络支持间的关系具有显著的调节作用,平均每周上网时间越多或平均自尊水平越高的班级,交往偏好对网络支持的正向预测作用越强。
(7)学校变量对大学生网络利他行为影响的多层线性分析结果表明：信息偏好对网络利他行为总分和网络提醒的影响、游戏偏好对网络分享的影响均存在显著的学校差异；学校性质显著削弱了游戏偏好与网络分享间的正向关联,即与211大学相比,非211大学的学生游戏偏好与网络分享的正向关联程度更强。
本文的创新之处在于：(1)提出了大学生网络利他行为的心理结构模型；(2)采用多种心理测量理论和技术整合的方法编制高质量的大学生网络利他行为量表；(3)用MACS模型对量表进行DIF检测；(4)一元概化理论和多元概化理论同时运用于量表编制中；(5)采用多层线性模型对大学生网络利他行为进行实证研究。
Internet altruistic behavior refers to the voluntary behavior on the internet which benefit other people and the society and not expect any return. College students are the most concentrated community in internet use, internet has become an indispensable learning and life tool for college students, and undergraduates'internet altruistic behavior is very popular. But the research on undergraduates'internet altruistic behavior is seldom and lacks of assessment tools. Therefore, Research on undergraduates'internet altruistic behavior and attention to the internet's positive influence not only enrich the content of internet psychology, but also are beneficial to construct the healthy and civilized internet atmosphere, promote the harmony of undergraduates'interpersonal relationship, and provide the reference for college students' internet moral education.
Based on the construction of the theory of undergraduates'internet altruistic behavior and exploring the psychological structure of undergraduates'internet altruistic behavior, this dissertation developed a high-quality scale of internet altruistic behavior, and made an empirical study on its influence factors using the scale. As a result, this dissertation had two big tasks:one task was to develop the internet altruistic behavior scale of undergraduates. To ensure the high quality of the scale, various theories and techniques of psychological measurement such as Classical Test Theory (CTT), Generalizability Theory (GT), Differential Item Functioning (DIF), and Structural Equation Model (SEM) were used. The other task was to explore the influence factors of the undergraduates' internet altruistic behavior such as individual variables, class variables and school variables. Due to the nested data, the dissertation explored the class variables and school variables impacting on the undergraduates' internet altruistic behavior and the relationship between undergraduates'internet altruistic behavior and their internet-behavior preference using multilevel analysis. The research results outlined below:
(1) The results of Classical Test Theory showed that the internet altruistic behavior scale of undergraduates (IABSU) included 30 items four factors which named them internet-support, internet-guidance, internet-sharing and internet-reminding.
(2) Differential Item Functioning showed:IABSU had not gender DIF, but 4 items existed area DIF. After the 4 items were deleted, the scale retained 26 items.
(3) The results of Generalizability Theory indicated:it was good for the 4 dimentions of IABSU, which ensured high measure accuracy and good measure benefit. The item numbers of IABSU dimensions were right. The measure accuracy of IABSU and its 4 dimensions was high, which was suitable to explain by the norm-referenced test and the criterion-referenced test.
(4) The test of reliability and validity showed:the reliability and validity of IABSU were good, it could be used as an effective tool to assess the internet altruistic behavior of undergraduates.
(5) Confirmatory factor analysis and cross-validity test indicated that undergraduates'internet altruistic behavior had a multi-level multi-dimension structure which comprised four first-order factors and single second-order factor.
(6) Multilevel analysis of class variables influencing college students' internet altruistic behavior showed:Significant differences among classes existed in internet-games preference affecting the total score of IABSU, internet-support and internet-sharing, computer-mediated communication preference affecting internet-support and internet-information preference affecting internet-reminding. The girl rate and the average self-esteem in class could significantly predict class mean difference of internet-support. The girl rate or the average self-esteem in class was higher, the class mean of internet-support was higher. The average online time every week and the average self-esteem in class could significantly moderated the relationship between computer-mediated communication preference and internet-support. The average online time every week was more or the average self-esteem in class was higher, computer-mediated communication preference positively predicted internet-support better.
(7) Multilevel analysis of school variables influencing college students' internet altruistic behavior indicated:There were significant differences among schools existing in internet-information preference affecting the total score of IABSU and internet-reminding, internet-games preference affecting internet-sharing. School properties significantly weakened the positive correlation between internet-games preference and internet-sharing. Namely compared with 211-Project University, the positive correlation between internet-games preference and internet-sharing in Non-211-Project University was stronger.
The mainly innovation of this dissertation was:(1) it proposed the psychological structure of undergraduates'internet altruistic behavior; (2) it used various psychological measurement theories and techniques to develop a high-quality internet altruistic behavior scale of undergraduates; (3) it used MACS model to detect DIF; (4) Univariate Generalizability Theory and Multivariate Generalizability Theory were both applied to scale development; (5) Multilevel model was used to make an empirical study on the internet altruistic behavior.
本文在构建大学生网络利他行为的理论框架、探讨大学生网络利他行为的心理结构模型的基础上,编制了较高质量的大学生网络利他行为量表,并以此量表为工具对大学生网络利他行为的影响因素进行了实证研究。因此,本文主要有两大研究任务。一个任务是编制大学生网络利他行为量表。为确保量表的高质量,本文采用了经典测量理论(CTT)、概化理论(GT)、项目功能差异分析(DIF)、结构方程模型(SEM)等多种心理测量理论和技术相整合的方法。另一任务是探讨影响大学生网络利他行为的个体变量、班级变量和学校变量因素。由于数据存在嵌套关系,本文采用了多层线性分析技术,分别探讨了班级变量和学校变量对大学生网络利他行为及其与网络行为偏好间关系的影响。具体研究结果概述如下：
(1)经典测量理论的研究结果表明：大学生网络利他行为量表(IABSU)包含30个项目,共有4个因子,分别将其命名为网络支持、网络指导、网络分享和网络提醒。
(2)项目功能差异分析结果表明：IABSU不存在性别DIF,但有4个项目存在地域DIF,删除这4个项目后,量表保留26个项目。
(3)概化理论分析结果表明：IABSU取4个维度是较合适的,既能保证较高的测量精度,又有较好的测量效益；IABSU各维度项目数量的设定比较合适；IABSU的4个维度及其整体的测量精度都很高,既可用于常模参照测验,也可用于标准参照测验。
(4)信效度的检验结果表明：IABSU的信度、效度很好,可以作为大学生网络利他行为的有效测评工具。
(5)验证性因素分析和交互效度检验结果表明：大学生网络利他行为是一个多层次多维度的结构,它是一个二阶单因素一阶4因素的结构模型。
(6)班级变量对大学生网络利他行为影响的多层线性分析结果表明：游戏偏好对网络利他行为总分、网络支持和网络分享的影响、交往偏好对网络支持的影响、信息偏好对网络提醒的影响均存在显著的班级差异；班级女生率和班级平均自尊水平对网络支持的班级均值差异有显著的预测作用,女生率或平均自尊水平越高的班级,网络支持的班级平均分数就越高。班级平均每周上网时间和班级平均自尊水平对交往偏好与网络支持间的关系具有显著的调节作用,平均每周上网时间越多或平均自尊水平越高的班级,交往偏好对网络支持的正向预测作用越强。
(7)学校变量对大学生网络利他行为影响的多层线性分析结果表明：信息偏好对网络利他行为总分和网络提醒的影响、游戏偏好对网络分享的影响均存在显著的学校差异；学校性质显著削弱了游戏偏好与网络分享间的正向关联,即与211大学相比,非211大学的学生游戏偏好与网络分享的正向关联程度更强。
本文的创新之处在于：(1)提出了大学生网络利他行为的心理结构模型；(2)采用多种心理测量理论和技术整合的方法编制高质量的大学生网络利他行为量表；(3)用MACS模型对量表进行DIF检测；(4)一元概化理论和多元概化理论同时运用于量表编制中；(5)采用多层线性模型对大学生网络利他行为进行实证研究。
Internet altruistic behavior refers to the voluntary behavior on the internet which benefit other people and the society and not expect any return. College students are the most concentrated community in internet use, internet has become an indispensable learning and life tool for college students, and undergraduates'internet altruistic behavior is very popular. But the research on undergraduates'internet altruistic behavior is seldom and lacks of assessment tools. Therefore, Research on undergraduates'internet altruistic behavior and attention to the internet's positive influence not only enrich the content of internet psychology, but also are beneficial to construct the healthy and civilized internet atmosphere, promote the harmony of undergraduates'interpersonal relationship, and provide the reference for college students' internet moral education.
Based on the construction of the theory of undergraduates'internet altruistic behavior and exploring the psychological structure of undergraduates'internet altruistic behavior, this dissertation developed a high-quality scale of internet altruistic behavior, and made an empirical study on its influence factors using the scale. As a result, this dissertation had two big tasks:one task was to develop the internet altruistic behavior scale of undergraduates. To ensure the high quality of the scale, various theories and techniques of psychological measurement such as Classical Test Theory (CTT), Generalizability Theory (GT), Differential Item Functioning (DIF), and Structural Equation Model (SEM) were used. The other task was to explore the influence factors of the undergraduates' internet altruistic behavior such as individual variables, class variables and school variables. Due to the nested data, the dissertation explored the class variables and school variables impacting on the undergraduates' internet altruistic behavior and the relationship between undergraduates'internet altruistic behavior and their internet-behavior preference using multilevel analysis. The research results outlined below:
(1) The results of Classical Test Theory showed that the internet altruistic behavior scale of undergraduates (IABSU) included 30 items four factors which named them internet-support, internet-guidance, internet-sharing and internet-reminding.
(2) Differential Item Functioning showed:IABSU had not gender DIF, but 4 items existed area DIF. After the 4 items were deleted, the scale retained 26 items.
(3) The results of Generalizability Theory indicated:it was good for the 4 dimentions of IABSU, which ensured high measure accuracy and good measure benefit. The item numbers of IABSU dimensions were right. The measure accuracy of IABSU and its 4 dimensions was high, which was suitable to explain by the norm-referenced test and the criterion-referenced test.
(4) The test of reliability and validity showed:the reliability and validity of IABSU were good, it could be used as an effective tool to assess the internet altruistic behavior of undergraduates.
(5) Confirmatory factor analysis and cross-validity test indicated that undergraduates'internet altruistic behavior had a multi-level multi-dimension structure which comprised four first-order factors and single second-order factor.
(6) Multilevel analysis of class variables influencing college students' internet altruistic behavior showed:Significant differences among classes existed in internet-games preference affecting the total score of IABSU, internet-support and internet-sharing, computer-mediated communication preference affecting internet-support and internet-information preference affecting internet-reminding. The girl rate and the average self-esteem in class could significantly predict class mean difference of internet-support. The girl rate or the average self-esteem in class was higher, the class mean of internet-support was higher. The average online time every week and the average self-esteem in class could significantly moderated the relationship between computer-mediated communication preference and internet-support. The average online time every week was more or the average self-esteem in class was higher, computer-mediated communication preference positively predicted internet-support better.
(7) Multilevel analysis of school variables influencing college students' internet altruistic behavior indicated:There were significant differences among schools existing in internet-information preference affecting the total score of IABSU and internet-reminding, internet-games preference affecting internet-sharing. School properties significantly weakened the positive correlation between internet-games preference and internet-sharing. Namely compared with 211-Project University, the positive correlation between internet-games preference and internet-sharing in Non-211-Project University was stronger.
The mainly innovation of this dissertation was:(1) it proposed the psychological structure of undergraduates'internet altruistic behavior; (2) it used various psychological measurement theories and techniques to develop a high-quality internet altruistic behavior scale of undergraduates; (3) it used MACS model to detect DIF; (4) Univariate Generalizability Theory and Multivariate Generalizability Theory were both applied to scale development; (5) Multilevel model was used to make an empirical study on the internet altruistic behavior.
引文
安晓璐.浅析虚拟社区中的利他行为.传媒观察,2005(3)：43—44.
安哲锋,骆方,张厚粲.多元概化理论在评定量表编制中的作用——以音像教材测评数据分析为例.心理科学,2008,31(5)：1192—1194.
蔡艳,陈抚良.多元概化理论在教育评估信度分析中的应用研究.江西师范大学学报(自然科学版),2007,31(3)：306—310.
陈平雁,黄浙明.SPSS10.0统计软件高级应用教程.北京：人民军医出版社,2004：56—68.
陈希镇.如何正确使用信度估计公式.心理学报,1991,23(1)：34—45.
程乐华.网络心理行为公开报告.广东经济出版社,2002：163—169.
丁芳.儿童的道德判断、移情与亲社会行为的关系研究.山东师大学报(社科版),2000,28(5)：77—81.
丁迈,陈曦.网络环境下的利他行为研究.现代传播,2009(3)：35—37.
范津砚,叶斌,章震宇等.探索性因素分析——最近10年的评述.心理科学进展,2003,11(5)：579—585.
顾海根.学校心理测量学.南宁：广西教育出版社,1999：50—55.
顾海根.心理与教育测量.北京：北京大学出版社,2008：192—194.
郭伯良,王燕,张雷.班级环境变量对儿童社会行为与学校适应间关系的影响.心理学报,2005,37(2)：233—239.
郭永玉.人格心理学——人性及其差异的研究.北京：中国社会科学出版社,2005：438—459.
郭玉锦,王欢.网络社会学.北京：中国人民大学出版社,2005：148.
何立国,周爱保.“青少年学生生活满意度量表”的概化理论研究.心理科学,2006,29(5)：1199—1202.
洪丽.高中生利他行为与移情、道德判断关系研究.福建师范大学硕士论文,2005.
洪自强,涂冬波.领导干部结构化面试信度的多元概括化理论分析.心理学探新,2006,26(1)：85—90.
候杰泰.信度与度向性：高alpha量表不一定是单度向.香港教育学报,1995,23(1)：135—146.
候杰泰,温忠麟,成子娟.结构方程模型及其应用.北京：教育科学出版社,2004：154—165.
胡显勇.GT在作文评分误差控制中的初步应用.心理科学,1994,17(2)：82—88.
胡月星,刘轩,赵郝锐.概化理论在结构化面试评分误差中的应用研究.西北师大学报(社会科学版),2006,43(4)：62—65.
胡中锋,莫雷.论因素分析方法的整合.心理科学,2002,25(4)：474—475.
江光荣,林孟平.班级环境与学生适应性的多层线性模型.心理科学,2005,28(6)：1443—1448.
金瑜.心理测量.上海：华东师范大学出版社,2001：251—258.
雷雳,杨洋.青少年病理性互联网使用量表的编制与验证.心理学报,2007,39(4)：688—69.
雷雳,柳铭心.青少年的人格特征与互联网社交服务使用偏好的关系.心理学报,2005,37(6)：797—80.
雷雳,王燕,郭伯良,张雷.班级行为范式对个体行为与受欺负关系影响的多层分析.心理学报,2004,36(5)：563—567.
李丹.儿童亲社会行为发展研究述评.心理科学,2001,24(2)：202—204.
李丹,李伯黍.儿童利他行为发展的实验研究.心理科学通讯,1989(5)：6—11.
李琼,倪玉菁,萧宁波.教师变量对小学生数学学习观影响的多层线性分析.心理发展与教育,2007(2)：93—99.
李婉,郝新春.校园网中大学生利他行为初探.今日南国,2008(7)：194—195.
刘红云.α系数与测验的同质性.心理科学,2008,31(1)：185—188.
刘红云,孟庆茂.教师背景变量对教师教学效果影响的多层线性分析.心理发展与教育,2002(4)：70—75.
刘红云,孟庆茂,张雷.班主任教师班级管理效能感对学生学习态度及其与学业效能间关系的影响.心理发展与教育,2005(2)：62—67.
刘红云,孟庆茂,张雷.教师集体效能和自我效能对工作压力影响作用的调节——多水平分析研究.心理科学,2004,27(5)：1073—1076.
刘远我,张厚粲.概化理论在作文评分中的应用研究.心理科学,2004,27(4)：955—957.
刘远我,张厚粲.面试评分中的误差分析研究.心理科学,1999,22(5)：447—448.
卢晓红.网络道德教育应关注网络亲社会行为.职业技术教育(教学版),2006,26(27)：115—117.
路海东.社会心理学.长春：东北师范大学出版社,2002.
罗发友,刘伶俐,刘友金.概化理论在高校教师教学水平测评中的应用研究.内蒙古农业大学学报(社会科学版),2002,4(4)：61—63.
骆方,张厚粲.检验项目功能差异的两类方法—CFA和IRT的比较.心理学探新,2006,26(1)：74—78.
彭茹静.利他主义行为的理论发展研究.江西社会科学,2003(7)：221—223.
彭庆红,樊富珉.大学生网络利他行为及其对高校德育的启示.思想理论教育导刊,2005(12)：49—51.
漆书青,戴海崎.现代教育与心理测量学原理.北京：高等教育出版社,2002.
秦磊,袁登华.概化理论在绩效评估中的应用.心理科学,2005,28(3)：650—651.
邱皓政.量化研究与统计分析(2版).台北：五南图书公司,2002.
邱浩政,林碧芳.结构方程模型的原理与应用.北京：中国轻工业出版社,2009.
任志洪.核心自我评价、班级环境对中学生抑郁影响的多层线性模型研究.福建师范大学硕士论文,2007.
孙晓敏,张厚粲.薛刚.多元概化理论在结构化面试中的应用研究.心理科学,2009,32(4)：916—919.
王振宇等.儿童社会化与教育.北京：人民出版社,1992：145.
王小璐,风笑天.网络中的青少年利他行为新探.广东青年干部学院学报,2004,18(3)：16—19.
汪向东,王希林,马弘.心理卫生评定量表手册(增订版).北京：中国心理卫生杂志社,1999：318—320.
温忠麟,侯杰泰,马什赫伯特.结构方程模型检验：拟合指数与卡方准则.心理学报,2004,
36(2)：186—194.
危敏.大学生网络亲社会行为的研究.山东大学硕士论文,2007.
吴明隆.SPSS统计应用实务：问卷分析与应用统计.北京：科学出版社,2003：109.
吴明隆.结构方程模型——AMOS的操作与应用.重庆：重庆大学出版社,2009：465—475.
夏学銮.整合社会心理学.郑州：河南人民出版社,1998：280.
谢小庆.信度估计的γ系数.心理学报,1998,30(2)：193—196.
S. E. Taylor, L. A. Peplau, D.O. Sears著.谢晓非,谢冬梅,张怡玲等译.社会心理学.北京：北京大学出版社(第十版),2004：379—392.
Pahicia Wallace著.谢影,苟建新译.互联网心理学.北京：中国轻工业出版社,2001：211.
严芳.用多元概化理论(MGT)分析国家公务员录用面试中的评分者信度.华东师范大学硕士论文,2002.
燕娓琴,谢小庆译.教育与心理测试标准.沈阳：沈阳出版社,2003.
杨志明,张雷.测评的概化理论及其应用.北京：教育科学出版社,2003.
杨志明,张雷.韦氏儿童智力量表能否测量第3因子——WISC-CR的多元概化理论研究.心理科学,2003,26(2)：305—307.
杨志明,张雷.用多元概化理论对普通话的测试.心理学报,2002,34(1)：50—55.
余兰.大学生交往中的网络角色研究.西南大学硕士论文,2007.
张广磊,邓光辉.网络游戏行为偏好与EPQ人格特质的关系研究.中国临床心理学杂志,2009,17(2)：225—226.
张雷,侯杰泰,何伟杰等.普通话测试的录音评分可行性、信度及经济效率.心理学报,2001,33(2)：97—103.
张雷,雷雳,郭伯良.多层线性模型应用.北京：教育科学出版社,2003.
赵必华,顾海根.运用均数与协方差结构模型侦查项目功能差异.心理发展与教育,2009(3)：119—122.
赵必华.量表编制与测量等价性检验：基于中学生自我概念量表.上海师范大学博士论文,2009.
郑丹丹,凌智勇.网络利他行为研究——以5Q地带“供种”行为为例.浙江学刊.2007(4)：179-185.
郑显亮,顾海根,竺培梁.“情绪智力量表(EIS)”的多元概化理论分析.心理科学,2009,32(1)：181—183.
David R.Shaffer著.邹泓等译.发展心理学——儿童与青少年(第六版).北京：中国轻工业出版社,2005：521-526.
周林,顾海根.上海市大学生网络行为偏好的实证研究.心理科学,2008,31(6)：1353—1356.
中国互联网络信息中心.中国互联网络发展状况统计报告.2001年1月.http://www.cnnic.cn/ uploadfiles/pdf/2010/1/15/101600.pdf.
Albert Kienfle Liau, Angeline Khoo & Peng Hwaang. (2005). Factors influencing adolescents engagement in risky internet behavior. Cyberpsychology & Behavior. Vol(8) 6,513-520.
Amichai-Hamburger, Yair. (2008). Potential and promise of online volunteering. Computers in Human Behavior. Vol 24(2),544-562.
Anderson J C, Gerbin D W. (1988). Structural equation modeling inpractice:A review and recommended two-step approach, Psychological Bulletin,103(3),411-423.
Angoff, W. H. (1993). Perspectives on differential item functioning methodology. In P. W. Holland & H. Wainer (Eds.), Differential item functioning (pp.3-23). Hillsdale, NJ:Erlbaum.
Arnold H J, Feldman D C. (1981). Social desirability response bias in self-report choice situations. Academy of Management Journal,24(2),377-383.
Bagozzi, R. P.,& Phillips, L. W. (1982). Representing and testing organizational theories:A holistic construal. Administrative Science Quarterly,27,459-489.
Bagozzi R P, Yi Y. (1988). On the evaluation of structural equation models. Journal of Academic of Marketing Science,16,74-94.
Barron, G,& Yechiam, E. (2002). Private e-mail requests and the diffusion of responsibility. Computers in Human Behavior,18,507-520.
Bar-Tal D. (1986). Altruistic motivation. Humbold Journal of Social Relation,13,3-14.
Baston, C. D. (1987). Prosocial motivation:Is it ever truly altruistic? Social Psychology (Vol.20, pp.65-122). New York:Academic Press.
Batson CD. (1991). The altruism question-Toward a Social Psychological Answer. Erlbaum: Hillsdale NJ,2-108.
Batson C D, Fultz J, Schoenrade P A. (1987). Distress and empathy:Two qualitatively distinct vicarious emotions with different motivational consequences. Journal of Personality,55,21-39.
Bentler P M, Bonett D G. (1980). Significant tests and goodness of fit in the analysis of covariance structures. Psychological Bulletin,8,588-606.
Brennan R L. (2000). Conceptions About Generalizability Theory EM:IP,1,5-10.
Brennan R L. (1992). An NCME instructional module on generalizability theory. Educational Measurement:Issues and Practice,27-34.
Brennan R L., Eugene G. Johnson. (1995). Generalizability of performance assessments. Educational Measurement,14(1),9-12.
Bryk, A. S.,& Raudenbush, S. W. (1992). Hierarchical linear models:Applications and data analysis methods. Newbury Park, CA:Sage Publications.
B. Latane & J. Darley. (1970). The Unresponsive Bystander:Why Doesn't He Help? New York: Appleton-Century-crofts.
B.F.P. Broekman, S.Z. Nyunt, M. Niti. (2008). Differential item functioning of the Geriatric Depression Scale in an Asian population. Journal of Affective Disorders,8,285-290.
Cadenhead, A. C.,& Richman, C. L.(1996). The effects of interpersonal trust and group status on prosocial and aggressive behaviors. Social Behavior and Personality,24,169-184.
Camilli G, Shepard LA. (1994). Methods for identifying biased test items. Thousand Oaks, CA: Sage.
Carrie A. Blair, Lori Foster Thompson & Karl L. Wuensch. (2005). Electronic Helping Behavior: The Virtual Presence of Others Makes a Difference. BASIC AND Applied Social Psychology, 27(2),171-178.
Chan D. (2000). Detection of Differential Item functioning on the Kirton Adaption-Innovation Inventory Using Multiple-Group Mean and Covariance Structure Analysis. Multivariate Behavioral Research,35(2),169-199.
Chih-Chien Wang & Chia-Hsin Wang. (2008). Helping Others in Online Games:Prosocial Behavior in Cyberspace. Cyberpsychology & Behavior,11(3),344-346.
Clauser BE, Mazor KM. (1998). Using statistical procedures to identify differentially functioning test items. Educ Measure Issues Pract,2,31-44.
Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Hillsdale, NJ. Eribaum.
Colleen Christensen, Deborah Fierst, April Jodocy, Dennis N. Lorenz. (1998). Answering the Call for Prosocial Behavior. The Journal of Social Psychology,138(5),564-571.
Crane PK, Van Belle G, Larson EB. (2004). Test bias in a cognitive test:differential item functioning in the CASI. Stat Med,23(2),241-256.
Deutsch, F. M.& Lamberti, D. M. (1986). Does social approval increase helping? Personality and Social Psychology Bulletin,12,149-157.
Eagly. A. H.,& Crowley, M. (1986). Gender and helping behavior:A meta-analytic review of the social psychological literature. Psychological Bulletin,11,3-22.
Eisenberg N., Fabes, R. A. (1998). Contemporaneous and longitudinal prediction of children's sympathy from disposition regulation and emotionality. Developmental Psychology,4,910-924
Eisenberg N. Miller P. (1998). The Role of Sympathy and Altruistic Personality Traits in Helping: A Reexamination. Journal of Personality,1,52-57.
Elainie A. Madsen, Richard J. Tunney. (2007). George Fieldman. Kinship and altruism:A cross-cultural experimental study. The British Psychological Society,8,339-359.
Everson, H. T., Millsap, R. E.,& Rodriguez, C. M. (1991). Isolating gender differences in test anxiety:A confirmatory factor analysis of the test anxiety inventory. Educational and Psychological Measurement,51,243-251.
Fabrigar, L. R., Wegener, D. T., MacCallum, R. C.& Strahan, E. J. (1999). Evaluating the use of exploratory factor analysis in psychological research. Psychological methods,4,272-299.
Ferrando, P. (1996). Calibration of invariant item parameters in a continuous item response model using the extended Lisrel measurement submodel. Multivariate Behavioral Research,31,419-439.
Flanagan, C. A., Bowes, J. M., Jonsson, B., Csapo, B.,& Sheblanova, E. (1998). Ties that bind: Correlates of adolescents'civic commitments in seven countries. Journal of Social Issues,54, 457-475.
Fornell, C.,& Larcker, D. F. (1981). Evaluating structural equation models with unobserved variables and measurement error. Journal of Marketing Research,18,39-50.
Ganster D C, (1983). Hennessey H W, Luthans F. Social desirability response effects:three alternative models. Academy of Management Journal,26(2),321-331.
George A. Marcoulides. (1989). The application of generalizability analysis to observational studies. Quality & Quantity 23,115-127.
Geory W. Alpers, Andrew J. Winzelberg, Catherine Classen. (2005). Evaluation of computerized text analysis in an internet breast cancer support group. Computers in Human Behavior,21,351-376.
Gross, A.E.& Mcmuller, P.A., (1982). Proeesses of Seeking for Help. In V.J. Derlega & J. Grzelak (edited), Cooperation and Helping Behaviour:Theories and Researeh. New York:Academic Press.
Hair J F, Anderson R E, Thatam R L & Black W C. (1998). Multivariate Data Analysis. NY; Prentice-Hall International, INC.
Hair, J. F. Jr., Black, W. C., Babin, B. J., Anderson, R. E.,& Tatham, R. L.(2006). Multivariate data analysis (6th ed.). Upper Saddle River, NJ:Prentice-Hall.
Hay D. F., Caplan, M., Castle, J.,& Stimson, C. A. (1991). Does sharing become increasingly "rational" in the second year of life? Developmental Psychology,27,987-993.
Hoffman. (1975). Developmental Synthesis of Effect and Cognition and its Implication for Altruistic Motivation. Developmental Psychology,11,605-622.
Holland PW, Wainer H, (1993). Differential item functioning. Hillsdale, NJ:Lawrence Erlbaum Associates.
Hoyle R. (1995). Structural equation modeling:concepts, issues and applications. Thousand Oaks, CA:Sage Publications.
Inwon Kang, Kun Chang Lee, Sangjae Lee, Jiho Choi. (2007). Investigation of online community voluntary behavior using cognitive map. Computers in human behavior,23 (1),111-126.
James B L. (2002). New York University, Inducing volunteer community service in undergraduates:The relative contributions of prior experience, coursework, and the dispositions of empathy and moral development,3,877-881.
Jeanne A. Teresi, John A. Fleishman. (2007). Differential item functioning and health assessment. Quality of Life Research,4.
Jeffrey P. Schloss, William B. Hurlbut. (2001). Altruism and altruistic love-science, philosophy, and religion in dialogue. Oxford:Oxford university Press,89-105.
Joseph O. Rentz. (1988). An Exploratory Study of the Generalizability of Selected Marketing Measures. Journal of the Academy of Marketing Science,16(1),141-150.
Joyce F. Benenson, Joanna Pascoe,& Nicola Radmore. (2007). Children's altruistic behavior in the dictator game. Evolution and Human Behavior,28,168-175.
J. M. Darley & C. D. Batson. (1973). "From Jerusalem to Jericho":A study of situational and dispositional variables in helping behavior. Journal of Personality and Social Psychohogy,27, 100-108.
J. P. Rushton. (1982). Social learning theory and the development of prosocial behavior, in:N. Eisenberg, Ed., The Development of Prosocial Behavior, London:Academic Press, Inc,83.
Kaiser, H. F. (1970). A second generation Little Jiffy. Psychometrika,35,401-415.
Kaiser H F. (1974). An index of factorial simplicity. Psychometrika,39(1),31-36.
Kaplan, D. (2000). Structural equation modeling:Foundations and extensions. Thousand Oaks, CA:Sage.
Karabenick, S. A.,& Knapp, J. R. (1988). Effects of computer privacy on help-seeking. Journal of Applied Social Psychology,18,461-472
Kimberly A. Hepner, Leo S. Morales, MD, Ron D. Hays. (2008). Evaluating differential item functioning of the PRIME-MD mood module among impoverished black and white women in primary care. Women's Health Issues,18,53-61.
Krebs, D. (1982). Altruism-a rational approach. In N. Eisenberg, ed., The development of prosocial behavior. New York:Academic Press,53-76.
K. E. Mathew, L. K. Canon. (1975). Environmental noise levels as a determinant of helping behavior. Journal of Personality and Social Psychology,32,571-577.
Lanning, K. (1991). Consistency, scalability and personality measurement. New York:Springer-Verlag.
Lind, G. (1989). The development of moral feelings through reason and dialog. In G. Lind & G. Pollitt-Gerlach, eds., Moral in'unmoralischer'Zeit. Heidelberg:Asanger,7-32.
MacCallum, R. C., Roznowski, M., Mar, M.,& Reith, J. V. (1994). Alternative strategies for cross-validation of covariance structure models. Multivariate Behavioral Research,29,1-32.
Markey, P. (2000). Bystander intervention in computer-mediated communication. Computers in Human Behavior,16,183-188.
Maria Orlando Grant N, Marshall. (2002). Differential item functioning in a Spanish translation of the PTSD checklist Detection and evaluation of impacts. Psychological Assessment,14(1),50-58.
McFarland L A. (2003). Warning Against Faking on a Personality Test Effects on Applicant Reactions and Personality Test Scores. International Journal of Selection and Assessment,4.
Mellenbergh, G J. (1982). Contingency table models for assessing item bias. Journal of Educational Statistics,7,105-118.
Mellenbergh, G. J. (1994). Generalized linear item response theory. Psychological Bulletin,115, 300-307.
Midlarsky, E. (1971). Aiding under stress:The effects of competence, dependency, visibility, and fatalism. Journal of Personality,39,132-149.
Mikyung Kim. (2001). Detecting DIF across the different language groups in a speaking test. Language Testing,18(1),89-114.
Millsap RE, Everson HT. (1993). Methodology review:statistical approaches for assessing measurement bias. Appl Psychol Meas,17,297-334.
Monica T. Whitty. (2002). Liar, liar! An examination of how open, supportive and honest people are in chat rooms. Computers in human behavior,18 (4),343-352.
Moore, C., Barresi, J., Thompson, C. (1998). The cognitive basis of future-oriented prosocial behavior. Social Development,7(2),198-218.
M. R. Cunningham. (1979). Weather, mood, and helping behavior:Quasi-experiments with the sunshine Samaritan. Journal of personality and social psychology,37,1947-1956.
Nubbaum, A. (1984). Multivariate generalizability theoy in educational measurement:An empirical study. Applied Psychological Measurement,8(2):219-230.
Nunnally JC, Bernstein IH. (1994). Psychometric Theory. New York:McGraw-Hill, INC. Oort,F.J. (1998). Simulation Study of item bias detection with restricted factor analysis. Structural Equation Modeling,5,107-124.
Paulhus D L. Social Desirable Responding:The Evolution of a Construct. In Braun H, Wiley D E, & Jackson D N (Eds.), Personality and intellect, validity and values:Cross-cutting themes. New York:Guilford,1999.
Pierre V, Gaston G & Richard B. (1992). The reliability of constructs derived from attitude-behavior theories:an application of generalizability theory in the health sector. Quality & Quantity,26,291-305.
P. L. Benson, S. A. Karabenick & M. Lerner, (1976). Pretty pleases:the effects of physical attractiveness, race, and sex on receiving help. Journal of Expreimental Social Psychology,12, 409-415.
Rajaratuam N, Cronbach L J, Gleser G C. (1965). Generalizabiblity of stratified-parallel Tests. Psychometrika,30(1),39-56.
Reise, S., Widaman, K.,& Pugh, R. (1993). Confirmatory factor analysis and item response theory: Two approaches for exploring measurement invariance. Psychological Bulletin,114,552-566.
Rheingold, H. L. (1982). Little children's participation in the work adults, a nascent prosocial behavior. Child Development,53,114-125.
Shelly E. Taylor, Letitia Anne Peplau, David O. Sears. (2004). Social Psychology. Peking University Press,383-400.
Shavelson R J, Webb N M. (1989). Generalizability Theory. American Psychologist,44(6),922-932.
Shavelson R J, Webb N M. (1991). Generalizability Theory:A Primer In:Jaeger R M. Measurement Methods for the Social Sciences Series. Sage Publications, INC.
Snijders T A B, Bosker R. (1994). Modeled variance in two-level models. Sociological Methods & Research,22,342-363.
Tai-Kuei Yu, Long-Chuan Lu & Tsai-Feng Liu. (2009). Exploring factors that influence knowledge sharing behavior via weblogs. Computers in Human Behavior,26,32-41.
Teresi JA. (2001). Statistical methods for examination of differential item functioning (DIF) with applications to cross-cultural measurement of functional, physical and mental health. J Mental Health Aging,7(1),31-40.
Thompson, B. (2000). Ten commandments of structural equation modeling. In L. G. Grimm & P. R. Yarnold (eds.), Reading and understanding more multivwriate statistics (pp.261-283). Washington, DC:American Psychological Association.
Trivers RL. (1971). The evolution of reciprocal altrter Review of Biology,46,35-37.
Wilson EO. (1975). The War between the words:biological versus social evolution and some related issues:Section2. Genetic basic of behavior-especially of altruism. American Psychologist,46,458-468.
Yechiam, E.,& Barron, G. (2003). Learning to ignore online help requests. Computational & Mathematical Organization Theory,9,327-339.
Yair Amichai-Hamburger. (2008). Potential and promise of online volunteering. Computers in human behavior,24 (2),544-562.
安哲锋,骆方,张厚粲.多元概化理论在评定量表编制中的作用——以音像教材测评数据分析为例.心理科学,2008,31(5)：1192—1194.
蔡艳,陈抚良.多元概化理论在教育评估信度分析中的应用研究.江西师范大学学报(自然科学版),2007,31(3)：306—310.
陈平雁,黄浙明.SPSS10.0统计软件高级应用教程.北京：人民军医出版社,2004：56—68.
陈希镇.如何正确使用信度估计公式.心理学报,1991,23(1)：34—45.
程乐华.网络心理行为公开报告.广东经济出版社,2002：163—169.
丁芳.儿童的道德判断、移情与亲社会行为的关系研究.山东师大学报(社科版),2000,28(5)：77—81.
丁迈,陈曦.网络环境下的利他行为研究.现代传播,2009(3)：35—37.
范津砚,叶斌,章震宇等.探索性因素分析——最近10年的评述.心理科学进展,2003,11(5)：579—585.
顾海根.学校心理测量学.南宁：广西教育出版社,1999：50—55.
顾海根.心理与教育测量.北京：北京大学出版社,2008：192—194.
郭伯良,王燕,张雷.班级环境变量对儿童社会行为与学校适应间关系的影响.心理学报,2005,37(2)：233—239.
郭永玉.人格心理学——人性及其差异的研究.北京：中国社会科学出版社,2005：438—459.
郭玉锦,王欢.网络社会学.北京：中国人民大学出版社,2005：148.
何立国,周爱保.“青少年学生生活满意度量表”的概化理论研究.心理科学,2006,29(5)：1199—1202.
洪丽.高中生利他行为与移情、道德判断关系研究.福建师范大学硕士论文,2005.
洪自强,涂冬波.领导干部结构化面试信度的多元概括化理论分析.心理学探新,2006,26(1)：85—90.
候杰泰.信度与度向性：高alpha量表不一定是单度向.香港教育学报,1995,23(1)：135—146.
候杰泰,温忠麟,成子娟.结构方程模型及其应用.北京：教育科学出版社,2004：154—165.
胡显勇.GT在作文评分误差控制中的初步应用.心理科学,1994,17(2)：82—88.
胡月星,刘轩,赵郝锐.概化理论在结构化面试评分误差中的应用研究.西北师大学报(社会科学版),2006,43(4)：62—65.
胡中锋,莫雷.论因素分析方法的整合.心理科学,2002,25(4)：474—475.
江光荣,林孟平.班级环境与学生适应性的多层线性模型.心理科学,2005,28(6)：1443—1448.
金瑜.心理测量.上海：华东师范大学出版社,2001：251—258.
雷雳,杨洋.青少年病理性互联网使用量表的编制与验证.心理学报,2007,39(4)：688—69.
雷雳,柳铭心.青少年的人格特征与互联网社交服务使用偏好的关系.心理学报,2005,37(6)：797—80.
雷雳,王燕,郭伯良,张雷.班级行为范式对个体行为与受欺负关系影响的多层分析.心理学报,2004,36(5)：563—567.
李丹.儿童亲社会行为发展研究述评.心理科学,2001,24(2)：202—204.
李丹,李伯黍.儿童利他行为发展的实验研究.心理科学通讯,1989(5)：6—11.
李琼,倪玉菁,萧宁波.教师变量对小学生数学学习观影响的多层线性分析.心理发展与教育,2007(2)：93—99.
李婉,郝新春.校园网中大学生利他行为初探.今日南国,2008(7)：194—195.
刘红云.α系数与测验的同质性.心理科学,2008,31(1)：185—188.
刘红云,孟庆茂.教师背景变量对教师教学效果影响的多层线性分析.心理发展与教育,2002(4)：70—75.
刘红云,孟庆茂,张雷.班主任教师班级管理效能感对学生学习态度及其与学业效能间关系的影响.心理发展与教育,2005(2)：62—67.
刘红云,孟庆茂,张雷.教师集体效能和自我效能对工作压力影响作用的调节——多水平分析研究.心理科学,2004,27(5)：1073—1076.
刘远我,张厚粲.概化理论在作文评分中的应用研究.心理科学,2004,27(4)：955—957.
刘远我,张厚粲.面试评分中的误差分析研究.心理科学,1999,22(5)：447—448.
卢晓红.网络道德教育应关注网络亲社会行为.职业技术教育(教学版),2006,26(27)：115—117.
路海东.社会心理学.长春：东北师范大学出版社,2002.
罗发友,刘伶俐,刘友金.概化理论在高校教师教学水平测评中的应用研究.内蒙古农业大学学报(社会科学版),2002,4(4)：61—63.
骆方,张厚粲.检验项目功能差异的两类方法—CFA和IRT的比较.心理学探新,2006,26(1)：74—78.
彭茹静.利他主义行为的理论发展研究.江西社会科学,2003(7)：221—223.
彭庆红,樊富珉.大学生网络利他行为及其对高校德育的启示.思想理论教育导刊,2005(12)：49—51.
漆书青,戴海崎.现代教育与心理测量学原理.北京：高等教育出版社,2002.
秦磊,袁登华.概化理论在绩效评估中的应用.心理科学,2005,28(3)：650—651.
邱皓政.量化研究与统计分析(2版).台北：五南图书公司,2002.
邱浩政,林碧芳.结构方程模型的原理与应用.北京：中国轻工业出版社,2009.
任志洪.核心自我评价、班级环境对中学生抑郁影响的多层线性模型研究.福建师范大学硕士论文,2007.
孙晓敏,张厚粲.薛刚.多元概化理论在结构化面试中的应用研究.心理科学,2009,32(4)：916—919.
王振宇等.儿童社会化与教育.北京：人民出版社,1992：145.
王小璐,风笑天.网络中的青少年利他行为新探.广东青年干部学院学报,2004,18(3)：16—19.
汪向东,王希林,马弘.心理卫生评定量表手册(增订版).北京：中国心理卫生杂志社,1999：318—320.
温忠麟,侯杰泰,马什赫伯特.结构方程模型检验：拟合指数与卡方准则.心理学报,2004,
36(2)：186—194.
危敏.大学生网络亲社会行为的研究.山东大学硕士论文,2007.
吴明隆.SPSS统计应用实务：问卷分析与应用统计.北京：科学出版社,2003：109.
吴明隆.结构方程模型——AMOS的操作与应用.重庆：重庆大学出版社,2009：465—475.
夏学銮.整合社会心理学.郑州：河南人民出版社,1998：280.
谢小庆.信度估计的γ系数.心理学报,1998,30(2)：193—196.
S. E. Taylor, L. A. Peplau, D.O. Sears著.谢晓非,谢冬梅,张怡玲等译.社会心理学.北京：北京大学出版社(第十版),2004：379—392.
Pahicia Wallace著.谢影,苟建新译.互联网心理学.北京：中国轻工业出版社,2001：211.
严芳.用多元概化理论(MGT)分析国家公务员录用面试中的评分者信度.华东师范大学硕士论文,2002.
燕娓琴,谢小庆译.教育与心理测试标准.沈阳：沈阳出版社,2003.
杨志明,张雷.测评的概化理论及其应用.北京：教育科学出版社,2003.
杨志明,张雷.韦氏儿童智力量表能否测量第3因子——WISC-CR的多元概化理论研究.心理科学,2003,26(2)：305—307.
杨志明,张雷.用多元概化理论对普通话的测试.心理学报,2002,34(1)：50—55.
余兰.大学生交往中的网络角色研究.西南大学硕士论文,2007.
张广磊,邓光辉.网络游戏行为偏好与EPQ人格特质的关系研究.中国临床心理学杂志,2009,17(2)：225—226.
张雷,侯杰泰,何伟杰等.普通话测试的录音评分可行性、信度及经济效率.心理学报,2001,33(2)：97—103.
张雷,雷雳,郭伯良.多层线性模型应用.北京：教育科学出版社,2003.
赵必华,顾海根.运用均数与协方差结构模型侦查项目功能差异.心理发展与教育,2009(3)：119—122.
赵必华.量表编制与测量等价性检验：基于中学生自我概念量表.上海师范大学博士论文,2009.
郑丹丹,凌智勇.网络利他行为研究——以5Q地带“供种”行为为例.浙江学刊.2007(4)：179-185.
郑显亮,顾海根,竺培梁.“情绪智力量表(EIS)”的多元概化理论分析.心理科学,2009,32(1)：181—183.
David R.Shaffer著.邹泓等译.发展心理学——儿童与青少年(第六版).北京：中国轻工业出版社,2005：521-526.
周林,顾海根.上海市大学生网络行为偏好的实证研究.心理科学,2008,31(6)：1353—1356.
中国互联网络信息中心.中国互联网络发展状况统计报告.2001年1月.http://www.cnnic.cn/ uploadfiles/pdf/2010/1/15/101600.pdf.
Albert Kienfle Liau, Angeline Khoo & Peng Hwaang. (2005). Factors influencing adolescents engagement in risky internet behavior. Cyberpsychology & Behavior. Vol(8) 6,513-520.
Amichai-Hamburger, Yair. (2008). Potential and promise of online volunteering. Computers in Human Behavior. Vol 24(2),544-562.
Anderson J C, Gerbin D W. (1988). Structural equation modeling inpractice:A review and recommended two-step approach, Psychological Bulletin,103(3),411-423.
Angoff, W. H. (1993). Perspectives on differential item functioning methodology. In P. W. Holland & H. Wainer (Eds.), Differential item functioning (pp.3-23). Hillsdale, NJ:Erlbaum.
Arnold H J, Feldman D C. (1981). Social desirability response bias in self-report choice situations. Academy of Management Journal,24(2),377-383.
Bagozzi, R. P.,& Phillips, L. W. (1982). Representing and testing organizational theories:A holistic construal. Administrative Science Quarterly,27,459-489.
Bagozzi R P, Yi Y. (1988). On the evaluation of structural equation models. Journal of Academic of Marketing Science,16,74-94.
Barron, G,& Yechiam, E. (2002). Private e-mail requests and the diffusion of responsibility. Computers in Human Behavior,18,507-520.
Bar-Tal D. (1986). Altruistic motivation. Humbold Journal of Social Relation,13,3-14.
Baston, C. D. (1987). Prosocial motivation:Is it ever truly altruistic? Social Psychology (Vol.20, pp.65-122). New York:Academic Press.
Batson CD. (1991). The altruism question-Toward a Social Psychological Answer. Erlbaum: Hillsdale NJ,2-108.
Batson C D, Fultz J, Schoenrade P A. (1987). Distress and empathy:Two qualitatively distinct vicarious emotions with different motivational consequences. Journal of Personality,55,21-39.
Bentler P M, Bonett D G. (1980). Significant tests and goodness of fit in the analysis of covariance structures. Psychological Bulletin,8,588-606.
Brennan R L. (2000). Conceptions About Generalizability Theory EM:IP,1,5-10.
Brennan R L. (1992). An NCME instructional module on generalizability theory. Educational Measurement:Issues and Practice,27-34.
Brennan R L., Eugene G. Johnson. (1995). Generalizability of performance assessments. Educational Measurement,14(1),9-12.
Bryk, A. S.,& Raudenbush, S. W. (1992). Hierarchical linear models:Applications and data analysis methods. Newbury Park, CA:Sage Publications.
B. Latane & J. Darley. (1970). The Unresponsive Bystander:Why Doesn't He Help? New York: Appleton-Century-crofts.
B.F.P. Broekman, S.Z. Nyunt, M. Niti. (2008). Differential item functioning of the Geriatric Depression Scale in an Asian population. Journal of Affective Disorders,8,285-290.
Cadenhead, A. C.,& Richman, C. L.(1996). The effects of interpersonal trust and group status on prosocial and aggressive behaviors. Social Behavior and Personality,24,169-184.
Camilli G, Shepard LA. (1994). Methods for identifying biased test items. Thousand Oaks, CA: Sage.
Carrie A. Blair, Lori Foster Thompson & Karl L. Wuensch. (2005). Electronic Helping Behavior: The Virtual Presence of Others Makes a Difference. BASIC AND Applied Social Psychology, 27(2),171-178.
Chan D. (2000). Detection of Differential Item functioning on the Kirton Adaption-Innovation Inventory Using Multiple-Group Mean and Covariance Structure Analysis. Multivariate Behavioral Research,35(2),169-199.
Chih-Chien Wang & Chia-Hsin Wang. (2008). Helping Others in Online Games:Prosocial Behavior in Cyberspace. Cyberpsychology & Behavior,11(3),344-346.
Clauser BE, Mazor KM. (1998). Using statistical procedures to identify differentially functioning test items. Educ Measure Issues Pract,2,31-44.
Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Hillsdale, NJ. Eribaum.
Colleen Christensen, Deborah Fierst, April Jodocy, Dennis N. Lorenz. (1998). Answering the Call for Prosocial Behavior. The Journal of Social Psychology,138(5),564-571.
Crane PK, Van Belle G, Larson EB. (2004). Test bias in a cognitive test:differential item functioning in the CASI. Stat Med,23(2),241-256.
Deutsch, F. M.& Lamberti, D. M. (1986). Does social approval increase helping? Personality and Social Psychology Bulletin,12,149-157.
Eagly. A. H.,& Crowley, M. (1986). Gender and helping behavior:A meta-analytic review of the social psychological literature. Psychological Bulletin,11,3-22.
Eisenberg N., Fabes, R. A. (1998). Contemporaneous and longitudinal prediction of children's sympathy from disposition regulation and emotionality. Developmental Psychology,4,910-924
Eisenberg N. Miller P. (1998). The Role of Sympathy and Altruistic Personality Traits in Helping: A Reexamination. Journal of Personality,1,52-57.
Elainie A. Madsen, Richard J. Tunney. (2007). George Fieldman. Kinship and altruism:A cross-cultural experimental study. The British Psychological Society,8,339-359.
Everson, H. T., Millsap, R. E.,& Rodriguez, C. M. (1991). Isolating gender differences in test anxiety:A confirmatory factor analysis of the test anxiety inventory. Educational and Psychological Measurement,51,243-251.
Fabrigar, L. R., Wegener, D. T., MacCallum, R. C.& Strahan, E. J. (1999). Evaluating the use of exploratory factor analysis in psychological research. Psychological methods,4,272-299.
Ferrando, P. (1996). Calibration of invariant item parameters in a continuous item response model using the extended Lisrel measurement submodel. Multivariate Behavioral Research,31,419-439.
Flanagan, C. A., Bowes, J. M., Jonsson, B., Csapo, B.,& Sheblanova, E. (1998). Ties that bind: Correlates of adolescents'civic commitments in seven countries. Journal of Social Issues,54, 457-475.
Fornell, C.,& Larcker, D. F. (1981). Evaluating structural equation models with unobserved variables and measurement error. Journal of Marketing Research,18,39-50.
Ganster D C, (1983). Hennessey H W, Luthans F. Social desirability response effects:three alternative models. Academy of Management Journal,26(2),321-331.
George A. Marcoulides. (1989). The application of generalizability analysis to observational studies. Quality & Quantity 23,115-127.
Geory W. Alpers, Andrew J. Winzelberg, Catherine Classen. (2005). Evaluation of computerized text analysis in an internet breast cancer support group. Computers in Human Behavior,21,351-376.
Gross, A.E.& Mcmuller, P.A., (1982). Proeesses of Seeking for Help. In V.J. Derlega & J. Grzelak (edited), Cooperation and Helping Behaviour:Theories and Researeh. New York:Academic Press.
Hair J F, Anderson R E, Thatam R L & Black W C. (1998). Multivariate Data Analysis. NY; Prentice-Hall International, INC.
Hair, J. F. Jr., Black, W. C., Babin, B. J., Anderson, R. E.,& Tatham, R. L.(2006). Multivariate data analysis (6th ed.). Upper Saddle River, NJ:Prentice-Hall.
Hay D. F., Caplan, M., Castle, J.,& Stimson, C. A. (1991). Does sharing become increasingly "rational" in the second year of life? Developmental Psychology,27,987-993.
Hoffman. (1975). Developmental Synthesis of Effect and Cognition and its Implication for Altruistic Motivation. Developmental Psychology,11,605-622.
Holland PW, Wainer H, (1993). Differential item functioning. Hillsdale, NJ:Lawrence Erlbaum Associates.
Hoyle R. (1995). Structural equation modeling:concepts, issues and applications. Thousand Oaks, CA:Sage Publications.
Inwon Kang, Kun Chang Lee, Sangjae Lee, Jiho Choi. (2007). Investigation of online community voluntary behavior using cognitive map. Computers in human behavior,23 (1),111-126.
James B L. (2002). New York University, Inducing volunteer community service in undergraduates:The relative contributions of prior experience, coursework, and the dispositions of empathy and moral development,3,877-881.
Jeanne A. Teresi, John A. Fleishman. (2007). Differential item functioning and health assessment. Quality of Life Research,4.
Jeffrey P. Schloss, William B. Hurlbut. (2001). Altruism and altruistic love-science, philosophy, and religion in dialogue. Oxford:Oxford university Press,89-105.
Joseph O. Rentz. (1988). An Exploratory Study of the Generalizability of Selected Marketing Measures. Journal of the Academy of Marketing Science,16(1),141-150.
Joyce F. Benenson, Joanna Pascoe,& Nicola Radmore. (2007). Children's altruistic behavior in the dictator game. Evolution and Human Behavior,28,168-175.
J. M. Darley & C. D. Batson. (1973). "From Jerusalem to Jericho":A study of situational and dispositional variables in helping behavior. Journal of Personality and Social Psychohogy,27, 100-108.
J. P. Rushton. (1982). Social learning theory and the development of prosocial behavior, in:N. Eisenberg, Ed., The Development of Prosocial Behavior, London:Academic Press, Inc,83.
Kaiser, H. F. (1970). A second generation Little Jiffy. Psychometrika,35,401-415.
Kaiser H F. (1974). An index of factorial simplicity. Psychometrika,39(1),31-36.
Kaplan, D. (2000). Structural equation modeling:Foundations and extensions. Thousand Oaks, CA:Sage.
Karabenick, S. A.,& Knapp, J. R. (1988). Effects of computer privacy on help-seeking. Journal of Applied Social Psychology,18,461-472
Kimberly A. Hepner, Leo S. Morales, MD, Ron D. Hays. (2008). Evaluating differential item functioning of the PRIME-MD mood module among impoverished black and white women in primary care. Women's Health Issues,18,53-61.
Krebs, D. (1982). Altruism-a rational approach. In N. Eisenberg, ed., The development of prosocial behavior. New York:Academic Press,53-76.
K. E. Mathew, L. K. Canon. (1975). Environmental noise levels as a determinant of helping behavior. Journal of Personality and Social Psychology,32,571-577.
Lanning, K. (1991). Consistency, scalability and personality measurement. New York:Springer-Verlag.
Lind, G. (1989). The development of moral feelings through reason and dialog. In G. Lind & G. Pollitt-Gerlach, eds., Moral in'unmoralischer'Zeit. Heidelberg:Asanger,7-32.
MacCallum, R. C., Roznowski, M., Mar, M.,& Reith, J. V. (1994). Alternative strategies for cross-validation of covariance structure models. Multivariate Behavioral Research,29,1-32.
Markey, P. (2000). Bystander intervention in computer-mediated communication. Computers in Human Behavior,16,183-188.
Maria Orlando Grant N, Marshall. (2002). Differential item functioning in a Spanish translation of the PTSD checklist Detection and evaluation of impacts. Psychological Assessment,14(1),50-58.
McFarland L A. (2003). Warning Against Faking on a Personality Test Effects on Applicant Reactions and Personality Test Scores. International Journal of Selection and Assessment,4.
Mellenbergh, G J. (1982). Contingency table models for assessing item bias. Journal of Educational Statistics,7,105-118.
Mellenbergh, G. J. (1994). Generalized linear item response theory. Psychological Bulletin,115, 300-307.
Midlarsky, E. (1971). Aiding under stress:The effects of competence, dependency, visibility, and fatalism. Journal of Personality,39,132-149.
Mikyung Kim. (2001). Detecting DIF across the different language groups in a speaking test. Language Testing,18(1),89-114.
Millsap RE, Everson HT. (1993). Methodology review:statistical approaches for assessing measurement bias. Appl Psychol Meas,17,297-334.
Monica T. Whitty. (2002). Liar, liar! An examination of how open, supportive and honest people are in chat rooms. Computers in human behavior,18 (4),343-352.
Moore, C., Barresi, J., Thompson, C. (1998). The cognitive basis of future-oriented prosocial behavior. Social Development,7(2),198-218.
M. R. Cunningham. (1979). Weather, mood, and helping behavior:Quasi-experiments with the sunshine Samaritan. Journal of personality and social psychology,37,1947-1956.
Nubbaum, A. (1984). Multivariate generalizability theoy in educational measurement:An empirical study. Applied Psychological Measurement,8(2):219-230.
Nunnally JC, Bernstein IH. (1994). Psychometric Theory. New York:McGraw-Hill, INC. Oort,F.J. (1998). Simulation Study of item bias detection with restricted factor analysis. Structural Equation Modeling,5,107-124.
Paulhus D L. Social Desirable Responding:The Evolution of a Construct. In Braun H, Wiley D E, & Jackson D N (Eds.), Personality and intellect, validity and values:Cross-cutting themes. New York:Guilford,1999.
Pierre V, Gaston G & Richard B. (1992). The reliability of constructs derived from attitude-behavior theories:an application of generalizability theory in the health sector. Quality & Quantity,26,291-305.
P. L. Benson, S. A. Karabenick & M. Lerner, (1976). Pretty pleases:the effects of physical attractiveness, race, and sex on receiving help. Journal of Expreimental Social Psychology,12, 409-415.
Rajaratuam N, Cronbach L J, Gleser G C. (1965). Generalizabiblity of stratified-parallel Tests. Psychometrika,30(1),39-56.
Reise, S., Widaman, K.,& Pugh, R. (1993). Confirmatory factor analysis and item response theory: Two approaches for exploring measurement invariance. Psychological Bulletin,114,552-566.
Rheingold, H. L. (1982). Little children's participation in the work adults, a nascent prosocial behavior. Child Development,53,114-125.
Shelly E. Taylor, Letitia Anne Peplau, David O. Sears. (2004). Social Psychology. Peking University Press,383-400.
Shavelson R J, Webb N M. (1989). Generalizability Theory. American Psychologist,44(6),922-932.
Shavelson R J, Webb N M. (1991). Generalizability Theory:A Primer In:Jaeger R M. Measurement Methods for the Social Sciences Series. Sage Publications, INC.
Snijders T A B, Bosker R. (1994). Modeled variance in two-level models. Sociological Methods & Research,22,342-363.
Tai-Kuei Yu, Long-Chuan Lu & Tsai-Feng Liu. (2009). Exploring factors that influence knowledge sharing behavior via weblogs. Computers in Human Behavior,26,32-41.
Teresi JA. (2001). Statistical methods for examination of differential item functioning (DIF) with applications to cross-cultural measurement of functional, physical and mental health. J Mental Health Aging,7(1),31-40.
Thompson, B. (2000). Ten commandments of structural equation modeling. In L. G. Grimm & P. R. Yarnold (eds.), Reading and understanding more multivwriate statistics (pp.261-283). Washington, DC:American Psychological Association.
Trivers RL. (1971). The evolution of reciprocal altrter Review of Biology,46,35-37.
Wilson EO. (1975). The War between the words:biological versus social evolution and some related issues:Section2. Genetic basic of behavior-especially of altruism. American Psychologist,46,458-468.
Yechiam, E.,& Barron, G. (2003). Learning to ignore online help requests. Computational & Mathematical Organization Theory,9,327-339.
Yair Amichai-Hamburger. (2008). Potential and promise of online volunteering. Computers in human behavior,24 (2),544-562.