Multiple Imputation in Mplus

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• Because the continuous are centered at their means, the intercept estimate (B 0 = 6.226) represents the adjusted mean for the group of employees that intend to stay on the job (TURNOVER = 0) • Controlling for other variables, employees that intend to quit (TURNOVER = 1) have a .640 lower job performance mean (B 4 = -.640, p < .001) • Holding other variables constant, one-point increase in wellbeing would produce a .417 increase in job performance, on average (B 1 = .417, p < .001)
! STANDARDIZED MODEL RESULTS! ! ! STDYX Standardization! ! JOBPERF ON! Beta Weights Two-Tailed! Estimate S.E. Est./S.E. P-Value! WBEING 0.390 0.051 7.720 0.000! JOBSAT 0.009 0.050 0.170 0.865! TENURE -0.043 0.042 -1.035 0.301! TURNOVER -0.238 0.042 -5.631 0.000!
Page 2 and 3: • Data set containing scores from
Page 4 and 5: • TITLE (optional) • DATA (same
Page 6 and 7: • All variables listed on the USE
Page 8 and 9: • Specifies characteristics of th
Page 10 and 11: DATA:! file = employee.dat;! VARIAB
Page 12 and 13: • Mplus saves each imputed data s
Page 14 and 15: • Mplus fully automates the analy
Page 16 and 17: SAMPLE STATISTICS! ! NOTE: These ar
Page 18 and 19: • The Wald statistic (a chi-squar
Page 22 and 23: ! R-SQUARE! ! ! Observed Two-Tailed
Page 24 and 25: • After creating the complete dat
Page 26: • Tabular presentations of missin

Multiple Imputation in Mplus

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