英语翻译4.1 Results and discussion .4.1.Reliability and validity

英语翻译
4.1 Results and discussion .4.1.Reliability and validity analysis .This study first extracted two factors that have eigenvalues of greater than 1 from the 7 items pertainingto a user’s attitude toward Internet advertisements,and these were entitled ‘‘truthful factor’’ and ‘‘pleasant factor’’.Then,these two factors and all measurement items in the questionnaire underwent reliability and validity analysis.Results are as shown in Table 1 and Appendix B.Alpha coefficients for ‘‘Internet advertising contact and attention’’ were 0.527; all other factors had reliability coefficients greater than 0.7—the overall Cronbach a reliability value is 0.920.The coefficients of factor analysis for our other scales were high,but the following items were dropped because of unacceptably low communalities:‘‘average time spent using the Internet per day (X1)’’,in the dimension ‘‘Internet advertising contact and attention’’,and‘‘Internetadvertisedproductsarevaluabletome(Y14)’’ in the dimension ‘‘Internet advertising attitude’’.Consequently factor-loading coefficients were in excess of 0.7,and the cumulative percent of variance for each factor dimension was greater than 50%,thereby indicating convergent validity.Harman’s one-factor test and correlation analysis was used to check for common variance bias.First,based on Harman’s one-factor test,all variables for any two factors are entered into a factor analysis.The results of the unrotated factor solutions indicate that more than one factor emerged in every test.We then used correlation analysis to account for all item-to-total correlation,and relationship between each two factors.Our results indicate that all item-to-total correlations are statistically significant,and each of these correlations are larger than the correlations between these two factors (see Table 1 andAppendix C).On the other hand,all correlations in Rxx and Ryy (measurement) are statistically significant,and each of these correlations are larger than all correlations in Rxy (example in Appendix D).The above tests provide evidence of discriminate validities and the measures have no common variance bias (Campbell & Fiske,1959;Fornell & Larcker,1981; Podsakoff & Organ,1986).This study has not included any controls in the model because no experimentation method was used.Demographic variables (e.g.age,sex,education etc.) were used as control variables as we analyzed variance through ANOVA; our results showed no significant difference between clusters that existed within the demographic variable;they,therefore,could not impact the relationship model,and the model could serve for general use (as shown inAppendix D).

4.1 结果和讨论 .4.1.可靠性和有效性分析This 研究第一次提取了有本征值大于1 从7 个项目pertainingto 用户的二个因素’对于互联网广告的s 态度,和这些被给权了 ‘‘真实的因素’’ 并且 ‘‘宜人的因素’’Then 、这两个因素和所有测量项目在查询表接受了可靠性和有效性分析.结果是依照被显示在表1 和附录B.Alpha 系数为 ‘‘互联网给联络和注意做广告’’ 是0.527; 所有其它因素有可靠性系数大于0.7—整体Cronbach 可靠性价值是0.920 .要素分析系数为我们的其它标度是高的,但以下项目投下了由于不能接受地低公社性:‘‘平均时间花费使用互联网每天(X1)’’,在维度 ‘‘互联网给联络和注意做广告’’,和‘‘Internetadvertisedproductsarevaluabletome(Y14)’’ 在维度 ‘‘互联网给态度做广告’’Consequently 因素装货系数是超出0.7,并且变化的渐增百分之为各个因素维度是大于50%,因此表明会聚validity.Harman’s 一因素测试和相关分析被使用检查共同的变化偏心.首先,根据Harman’s 一因素测试,所有可变物为任何二个因素参与要素分析.结果的unrotated 因素解答表明,超过一个因素涌现了在每个测试.我们然后曾经相关分析占所有项目对总交互作用,和关系在各二个因素之间.我们的结果表明,所有项目对总交互作用统计地是重大的,并且每个这些交互作用比交互作用大的在这两个因素之间(参见表1 andAppendix C) .另一方面,所有交互作用在Rxx 和Ryy (测量) 比所有交互作用统计地是重大,和每个这些交互作用大的在Rxy (例子在附录D) .上述测试提供证据歧视有效性并且措施没有共同的变化偏心(坎伯& Fiske,1959;Fornell & Larcker 1981 年; Podsakoff & 器官,1986).This 研究未包括任何控制在模型因为实验方法未被使用.人口统计的可变物(e.g.age,性,教育等.) 被使用了当控制可变物当我们分析了变化通过ANOVA; 我们的结果显示没有重大区别在存在在人口统计的variable;they 之内不能,因此,冲击关系模型,并且模型能为一般用途服务的群之间(作为被显示的inAppendix D) .
不是很准确,电脑翻译的..