Evaluation of Validity and Reliability of Diversity Icebreaker Questionnaire Tetyana Sydorenko Ladislaus von Bortkiewicz Chair of Statistics C.A.S.E. – Center for Applied Statistics and Economics Humboldt–Universität zu Berlin http://lvb.wiwi.hu-berlin.de http://www.case.hu-berlin.de
33
Embed
Evaluation of Validity and Reliability of Diversity …sfb649.wiwi.hu-berlin.de/lvb/hejnice2012/sydorenko_DI...Evaluation of Validity and Reliability of Diversity Icebreaker Questionnaire
This document is posted to help you gain knowledge. Please leave a comment to let me know what you think about it! Share it to your friends and learn new things together.
Transcript
Evaluation of Validity and Reliability ofDiversity Icebreaker Questionnaire
Tetyana Sydorenko
Ladislaus von Bortkiewicz Chair of StatisticsC.A.S.E. – Center for Applied Statisticsand EconomicsHumboldt–Universität zu Berlinhttp://lvb.wiwi.hu-berlin.dehttp://www.case.hu-berlin.de
Common factors in all data sets:� Preference for working with numbers v28, v31,� Preference for precise communication and decisions v8, v15,
v18, v35� Preference for being practical minded v20, v37
Problematic items: v1, v4, v11, v23, v25, v40
Evaluation of Diversity Icebreaker Questionnaire
Methods and Results 4-5
EFA for RED dimension
Norwegian German English
Horn 2 2 2Kaiser 4 4 4
Table 4: Number of factors for RED dimension
Common factors in all data sets:� Preference to be in a group: v2, v22, v42� Extraversion: v6, v26, v38� Consideration of other’s feelings: v14, v30, v32, v34
Unstable factor:� Preference for personal communication v9, v12, v16
Evaluation of Diversity Icebreaker Questionnaire
Methods and Results 4-6
EFA for GREEN dimension
Norwegian German English
Horn 4 3 1Kaiser 4 5 6
Table 5: Number of factors for GREEN dimension
Common factor in all data sets:� Creative ideas and solutions v33, v36, v39� Broader perspectives v7, v10, v17
Table 6: Number of factors for the whole item’s pool
� RED items loaded on one/two factors in all data sets� mixed factors containing BLUE and GREEN items
Evaluation of Diversity Icebreaker Questionnaire
Methods and Results 4-8
Two parameter Item Response Model (2PL)
P(Yij = 1 | θi ) =exp [αj(θi − δj)]
1 + exp [αj(θi − δj)]
� i = 1, . . . , n observations, j = 1, . . . , p items� θi latent trait of person i� δj difficulty of item j ,� αj discrimination power of item j
Goals:� Evaluation of item’s difficulty parameter and separation power
in BLUE/RED/GREEN sets� Estimation of δj , αi and detection of items which function
badlyEvaluation of Diversity Icebreaker Questionnaire
Methods and Results 4-9
2PL for BLUE dimension (German data)
Figure 1: ICC curves for BLUE items in German sample
Evaluation of Diversity Icebreaker Questionnaire
Methods and Results 4-10
2PL for BLUE dimension (English data)
Figure 2: ICC curves for BLUE items in English sample
Evaluation of Diversity Icebreaker Questionnaire
Methods and Results 4-11
2PL for RED dimension (German data)
Figure 3: ICC curves for RED items in German sample
Evaluation of Diversity Icebreaker Questionnaire
Methods and Results 4-12
2PL for RED dimension (English data)
Figure 4: ICC curves for RED items in English sample
Evaluation of Diversity Icebreaker Questionnaire
Methods and Results 4-13
2PL for GREEN dimension (German data)
Figure 5: ICC curves for GREEN items in German sample
Evaluation of Diversity Icebreaker Questionnaire
Methods and Results 4-14
2PL for GREEN dimension (English data)
Figure 6: ICC curves for GREEN items in English sample
Evaluation of Diversity Icebreaker Questionnaire
Methods and Results 4-15
Multiple Indicator Multiple Cause Model(MIMIC)
Is there any significant native speaker effect obBLUE/RED/GREEN dimensions (estimation of betaj)
P(Yij = 1) = G
{δj + αj
(∑k
βkxik + θi
)}
� xik covariate (e.g. gender, native speaker)� G link function (e.g. logistic function)� At the beginning: Confirmatory Factor Analysis (CFA)� Incorporation of covariate and comparison of model fit
Table 10: Model fit for three factor model in German sample
Evaluation of Diversity Icebreaker Questionnaire
Conclusions 5-1
Conclusions I
Reliability analysis� the GREEN dimension has the lowest value of Cronbach’s α
EFA for single dimension� Factor structure of RED items could be replicated in different
data sets� Different factor models for BLUE and GREEN dimensions in
different data setsEFA for whole item pool� RED items build single factor/factors� Mixed factors with BLUE and GREEN items in all datasets
Evaluation of Diversity Icebreaker Questionnaire
Conclusions 5-2
Conclusions II
2PL Model� RED items had on general higher separation power� More BLUE and GREEN items with low discrimination
coefficientsCFA and MIMIC for single dimension� Accaptable model fit only for the RED dimension� Covariate native speaker does not have significant influence on
RED latent traitCFA and MIMIC for whole item pool� Three factor model does not hold� Especially BLUE and GREEN items should be elaborated
Evaluation of Diversity Icebreaker Questionnaire
Evaluation of Validity and Reliability ofDiversity Icebreaker Questionnaire
Tetyana Sydorenko
Ladislaus von Bortkiewicz Chair of StatisticsC.A.S.E. – Center for Applied Statisticsand EconomicsHumboldt–Universität zu Berlinhttp://lvb.wiwi.hu-berlin.dehttp://www.case.hu-berlin.de
William O. Dunlap and John M. CornwellFactor analysis of ipsative measuresMultivariate Behavioural Research 29(1), 1994
Bjørn EkelundThe application of a model which integrates marketsegmentation and psychological theories to change energyconsumption in householdsHenley Management College, 1997
Bjørn Ekelund and Eva LangvikDiversity Icebreaker. How to Manage Diversity ProcessesHuman Factors Publishing, 2008