Sentences with phrase «missing predictor variables»

Therefore, among the 1,055 possible participants, 1,000 for Cooperation, 997 for Self - Control, and 1,026 for Assertion were available because of missing predictor variables or covariates at 2 years of age.

Not exact matches

Several analyses focused on missing data.36 To explore missing data patterns, we coded loss to follow - up as a binary variable and tested baseline variables as predictors using a stepwise logistic regression.

To assess the potential effect of missing data (ie, ignorable vs informative missing data), a pattern - mixture analysis was implemented using 2 - tailed tests.51 We defined patterns using a binary completer status variable, which was entered as a predictor in the RRM and MMANOVA.

We undertook multiple imputation (MI) of predictor variables to assess the sensitivity of results to missing data using the chained regression method of MI to generate five imputed data sets.

Baseline drinking status (ever vs never tried alcohol) did not predict attrition, but to account for attrition bias related to other variables, estimation was carried out after multiple imputation using the standard missing at random assumption (ie, missing data are assumed missing at random conditional on observed predictors included in the model).27 The imputation model included all the predictors in the alcohol models plus a number of auxiliary variables that were not of direct theoretical interest but were nonetheless predictive of missingness so as to improve the quality of the imputations and make the missing at random assumption more plausible.28

Multivariable regression models were considered, but the modest sample size and patterns of missing data did not allow for simultaneous consideration of multiple predictor variables.