Power analysis simulation for a planned missing data design

TITLE:

section 1.13 power analysis (r = .30);

MONTECARLO:

names are q1-q8;  ! variable names;

nobservations = 300;  ! sample size;

nreps = 5000;  ! number of artificial data sets;

seed= 56798;  ! random number seed;

patmiss = 

q1(0) q2(0) q3(0) q4(0) q5(0) q6(0) q7(1) q8(1)|

q1(0) q2(0) q3(0) q4(0) q5(1) q6(1) q7(0) q8(0)|

q1(0) q2(0) q3(1) q4(1) q5(0) q6(0) q7(0) q8(0);  ! specify missing data patterns;

patprobs = .333 | .333 | .334;  ! missing data pattern proportions;

MODEL POPULATION:

[q1 - q8*0]; ! population model and parameter values;

q1 - q8*1;

q1 - q8 with q1 - q8*.30;

ANALYSIS:

estimator = ml;

MODEL:

[q1 - q8*0];  ! analysis model;

q1 - q8*1;

q1 - q8 with q1 - q8*.30;

Questions or suggestions? Email Craig Enders