This function checks the validity of user specified parameters including rate parameters for count variables,
proportion parameters for binary and ordinary variables, mean and variance parameters for normal data, as well as the
validity of entries in the correlation matrix. This function also computes the lower and upper limits for each pairwise
correlation based on the marginal probabilities for range violation checks.
User specified correlation matrix for the multivariate data.
prop.vec.bin
Vector of probabilities corresponding to each of the binary variables.
prop.vec.ord
Vector of probabilities corresponding to each of the ordinal variables. For each of the ordinal variable,
the i-th element of the probability vector is the cumulative probability defining the marginal distribution
of the ordinal variable. If the variable has k categories, the i-th element of p will contain k-1 probabilities.
The k-th element is implicitly 1.
lamvec
Vector of rate parameters for the count variables.
nor.mean
Vector of means for the normal variables.
nor.var
Vector of variances for the normal variables.
Details
This function computes the lower and upper bounds for all possible pairs that involve count, binary, ordinal and normal variables.
Value
The function returns TRUE if no specification problem is encountered. Otherwise, it returns an error message.
References
Demirtas, H. and Hedeker, D. (2011). A practical way for computing approximate lower and upper
correlation bounds. The American Statistician, 65(2), 104-109.
Demirtas, H., Hedeker, D., and Mermelstein, R.J. (2012). Simulation of massive public health data
by power polynomials. Statistics in Medicine, 31(27), 3337-3346.