Input parameter

Explanation

SEED

Random number seed (should be a positive integer)

ALEVEL

Significance level of the statistical test (Type I error)

P

Event proportion (response probability)

NITER

Number of iterations performed

N_REPEAT

Number of iterations performed

^*NITER and N_REPEAT should be the same number

PATH

Directory in which results are saved

TABLE

Table name for saved results

R

Number of categorized groups

Example: continuous = 1, median = 2, tertile = 3, quantile = 4

^*If model includes nominal variables, R should be >1

CHANGE_POINT

Change point (see Figure 1)

Regression coefficients for the covariates in the full model, except for predictors and intercept, specified as:

MODEL_1

%NRSTR(α₁^*X1+, , + β_iX_i)

MODEL_2

%NRSTR(α₁^*(the value of change_point) + α₂^*(X1 − (the value of change_point) +, , + β_iX_i)

α and β are the given regression coefficient values

^*If model is linear, the regression coefficients α₁ and α₂ are the same

Sample size, mean, standard deviation, skewness, kurtosis, and correlation are specified as:

Example

DATA a (type=CORR);

LENGTH _TYPE_ $40;

INPUT _NAME_ $_TYPE_$ X1　X2 ;

IF TRIM(LEFT(_TYPE_))=’N’ THEN call symput(‘NSP’, X1);

CARDS;

. MEAN 70 50

. STD 4 5

. N 300 300

X1 CORR 1 0

X2 CORR 0 1

;

RUN;

^*If only one covariate is defined, the correlation should be set to 1. The sample size of all covariates should be the same.

SKW_KRT

%NRSTR ({skewness 1 kurtosis 1, skewness 2 kurtosis 2, })

^*If covariates are normally distributed, both skewness and kurtosis are set to 0.

LIST_VARNAME

%NRSTR (X1, X2, , Xi); list of variable names in A of above dataset

MIN

Minimum value of a continuous variable

MAX

Maximum value of a continuous variable

SUB_GROUP

Number of subgroups

CATEGORIZATION

%NRSTR (list of covariates to be categorized)

CATEGORIZATION_R

%NRSTR (list of new covariate names after categorization)

CONTI_MODEL

%NRSTR (list of covariates in a continuous logistic regression model)

^*Even if some parameters are not needed, please assign all parameters and specify necessary variables in a logistic regression model.