PhD Final Thesis April 2013.pdf - Anglia Ruskin Research Online

Thesis Keith Gale 20137.15 Interpretation of Stage One independent samples t-testsA test for equality (Levene, 1960) is used to determine whether the same variance ofscores occur for both groups. The outcome of this test decides which value to use forcalculating the effect size. If the Sig. value exceeds 0.05 then ‘equal variancesassumed’ is used. If the Sig. value is 0.05 or less, then ‘equal variances not assumed’value is used. The relevant t-test value is used to calculate effect size to provide anindication of the magnitude of difference between the groups. For all independent t-tests, an Eta squared formula is used to determine effect size with values between 0and 1 to represent the proportion of variance in the dependant variable comparedwith the independent group variable. The Eta squared formula is:Eta squared = t²t² + (N1 + N2 – 2)7.15.1 Interpretation for CSF1A – Starting on time:Cohen (1998) proposes guidelines for interpretation of the Eta squared values. Theseare: 0.01=Small differences, 0.06=Moderate difference, 0.14=Large difference.Eta squared for CSF1A = -1.088²-1.088² + (60 + 104 – 2)Eta squared for CSF1A = 0.007An independent t-test was used to compare the ‘starting on time’ critical successfactor scores for discrete verses framework projects. There was no significantdifference in scores for discrete projects (M=0.158, SD=0.014) and frameworkprojects (M=0.160, SD=0.014), t (162) =-1.088, p=0.278). The magnitude of thedifferences in the means was very small (0.007).153