Multiple imputation regression analysis (imputation phase)

TITLE:

section 8.15 data analysis example 2: multiple regression (diagnostic phase);

DATA:

file = employee.dat;

VARIABLE:

! id = employee id;

! age = employee age;

! tenure = years on the job;

! female = gender (0 = male, 1 = female);

! wbeing = psychological well-being;

! jobsat = job satisfaction

! jobperf = job performance;

! turnover = turnover intentions (0 = no, 1 = yes);

! iq = iq score;

names = id age tenure female wbeing jobsat jobperf turnover iq;

usevariables = age - iq;  ! variables in imputation model; 

missing = all (-99);

ANALYSIS:

type = basic; ! saturated imputation model;

bseed = 73293;

fbiterations = 5000;  ! total iterations;

DATA IMPUTATION:

impute = wbeing jobsat; ! variables to be imputed;

ndatasets = 50;  ! number of imputed data sets;

save = employeeimp*.dat;  ! filename prefix for imputed data;

thin = 100;  ! between-imputation iterations;

OUTPUT:

tech8;  ! PSR mcmc convergence diagnostic;

Questions or suggestions? Email Craig Enders