The HPLMIXED Procedure

MODEL Statement

  • MODEL dependent = <fixed-effects></ options>;

The MODEL statement names a single dependent variable and the fixed effects, which determine the bold upper X matrix of the mixed model. (For more information, see the section Parameterization of Model Effects. The MODEL statement is required.

An intercept is included in the fixed-effects model by default. If no fixed effects are specified, only this intercept term is fit. The intercept can be removed by using the NOINT option.

Table 3 summarizes options in the MODEL statement. These are subsequently discussed in detail in alphabetical order.

Table 3: Summary of Important MODEL Statement Options

Option Description
Model Building
NOINT Excludes the fixed-effect intercept from model
Statistical Computations
ALPHA=alpha Determines the confidence level (1 minus alpha) for fixed effects
DDFM= Specifies the method for computing denominator degrees of freedom
Statistical Output
CL Displays confidence limits for fixed-effects parameter estimates
SOLUTION Displays fixed-effects parameter estimates


You can specify the following options in the MODEL statement after a slash (/).

ALPHA=number

sets the confidence level to be 1 minusnumber for each confidence interval of the fixed-effects parameters. The value of number must be between 0 and 1; the default is 0.05.

CL

requests that t-type confidence limits be constructed for each of the fixed-effects parameter estimates. The confidence level is 0.95 by default; this can be changed with the ALPHA= option.

DDFM=NONE | RESIDUAL

specifies the method for computing the denominator degrees of freedom for the tests of fixed effects.

The DDFM=RESIDUAL option performs all tests by using the residual degrees of freedom, n minus normal r normal a normal n normal k left-parenthesis bold upper X right-parenthesis, where n is the number of observations used. It is the default degrees-of-freedom method.

DDFM=NONE specifies that no denominator degrees of freedom be applied. PROC HPLMIXED then essentially assumes that infinite degrees of freedom are available in the calculation of p-values. The p-values for t tests are then identical to p-values that are derived from the standard normal distribution. In the case of F tests, the p-values equal those of chi-square tests determined as follows: if upper F Subscript normal o normal b normal s is the observed value of the F test with l numerator degrees of freedom, then

p equals normal upper P normal r StartSet upper F Subscript l comma normal infinity Baseline greater-than upper F Subscript normal o normal b normal s Baseline EndSet equals normal upper P normal r StartSet chi Subscript l Superscript 2 Baseline greater-than l upper F Subscript normal o normal b normal s Baseline EndSet
NOINT

requests that no intercept be included in the model. (An intercept is included by default.)

SOLUTION
S

requests that a solution for the fixed-effects parameters be produced. Using notation from the section Linear Mixed Models Theory, the fixed-effects parameter estimates are ModifyingAbove bold-italic beta With caret and their approximate standard errors are the square roots of the diagonal elements of left-parenthesis bold upper X prime ModifyingAbove bold upper V With caret Superscript negative 1 Baseline bold upper X right-parenthesis Superscript minus.

Along with the estimates and their approximate standard errors, a t statistic is computed as the estimate divided by its standard error. The Pr greater-than |t| column contains the two-tailed p-value that corresponds to the t statistic and associated degrees of freedom. You can use the CL option to request confidence intervals for all of the parameters; they are constructed around the estimate by using a radius that is the product of the standard error times a percentage point from the t distribution.

Last updated: December 09, 2022