Stata 15 help for quadchk

[XT] quadchk -- Check sensitivity of quadrature approximation

Syntax

quadchk [#1 #2] [, nooutput nofrom ]

#1 and #2 specify the number of quadrature points to use in the comparison runs of the previous model. The default is to use approximately 2n_q/3 and 4n_q/3 points, where n_q is the number of quadrature points used in the original estimation.

Menu

Statistics > Longitudinal/panel data > Setup and utilities > Check sensitivity of quadrature approximation

Description

quadchk checks the quadrature approximation used in the random-effects estimators of the following commands:

xtcloglog xtintreg xtlogit xtologit xtoprobit xtpoisson, re with the normal option xtprobit xtstreg xttobit

quadchk refits the model for different numbers of quadrature points and then compares the different solutions. quadchk respects all options supplied to the original model except or, vce(), and the maximize_options.

Options

nooutput suppresses the iteration log and output of the refitted models.

nofrom forces refitted models to start from scratch rather than starting from the previous estimation results. Specifying the nofrom option can level the playing field in testing estimation results.

Remarks

As a rule of thumb, if the coefficients do not change by more than a relative difference of 10^-4 (0.01%), the choice of quadrature points does not significantly affect the outcome, and the results may be confidently interpreted. However, if the results do change appreciably -- greater than a relative difference of 10^-2 (1%) -- then you should question whether the model can be reliably fit using the chosen quadrature method and the number of integration points.

Two aspects of random-effects models have the potential to make the quadrature approximation inaccurate: large group sizes and large correlations within groups. These factors can also work in tandem, decreasing or increasing the reliability of the quadrature. Increasing the number of integration points increases the accuracy of the quadrature approximation.

Examples

Setup . webuse quad1 . xtset id

Fit random-effects (RE) probit model . xtprobit z x1-x6

Check stability of quadrature calculation . quadchk

Fit RE probit model using nonadaptive Gauss-Hermite quadrature . xtprobit z x1-x6, intmethod(ghermite)

Check stability of quadrature approximation, suppressing output of models . quadchk, nooutput

Same as above xtprobit, but increase the number of iteration points to 120 . xtprobit z x1-x6, intmethod(ghermite) intpoints(120)

Check stability of quadrature approximation, suppressing output of models . quadchk, nooutput


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