In this article, I derive a score test for the equality of one or more parameters across groups of observations following estimation of a single-index model. The test has a wide array of applications and nests Pearson’s chi-squared test as a particular case. The postestimation command scoregrp implements the test and works with logit, logistic, probit, poisson, or regress (see [R] logit, [R] logistic, [R] probit, [R] poisson, and [R] regress). Finally, I show some applications of the test
Results for the group 0 v group 2 balanced data set (Best Average Test Performance = 78.8% Best Aver...
Existing procedures for testing measurement invariance focus mainly on group-level comparisons rathe...
The applied statistician often encounters the need to compare two or more groups with respect to mor...
SUMMARY. We develop a score test statistic based on quasi-score functions for goodness of fit of gen...
The score test statistic computed using the observed information is easy to compute numerically. Its...
For the external-anchor test equating model, two observed-score methods are derived using the slope ...
In this paper, we consider a family of recently-proposed measurement invariance tests that are base...
In this paper we give the generalization of the score tests covering the case of ties and we give ex...
Results for group 0 v group 1 balanced data set (Best Average Test Performance = 67.9% and Best Aver...
In this paper, we derive score test statistics to discriminate between proportional hazards and prop...
Measurement invariance (MI) entails that measurements in different groups are comparable, and is a l...
Global tests provide a useful tool for comparing two or more groups with respect to multiple correla...
One of the most frequently used regression models for survival data was proposed by Sir David Cox in...
Results for group 1 v group 2 balanced data set (Best Average Test Performance = 61.5% and Best Aver...
For the external-anchor test equating model, two observed-score methods are derived using the slope...
Results for the group 0 v group 2 balanced data set (Best Average Test Performance = 78.8% Best Aver...
Existing procedures for testing measurement invariance focus mainly on group-level comparisons rathe...
The applied statistician often encounters the need to compare two or more groups with respect to mor...
SUMMARY. We develop a score test statistic based on quasi-score functions for goodness of fit of gen...
The score test statistic computed using the observed information is easy to compute numerically. Its...
For the external-anchor test equating model, two observed-score methods are derived using the slope ...
In this paper, we consider a family of recently-proposed measurement invariance tests that are base...
In this paper we give the generalization of the score tests covering the case of ties and we give ex...
Results for group 0 v group 1 balanced data set (Best Average Test Performance = 67.9% and Best Aver...
In this paper, we derive score test statistics to discriminate between proportional hazards and prop...
Measurement invariance (MI) entails that measurements in different groups are comparable, and is a l...
Global tests provide a useful tool for comparing two or more groups with respect to multiple correla...
One of the most frequently used regression models for survival data was proposed by Sir David Cox in...
Results for group 1 v group 2 balanced data set (Best Average Test Performance = 61.5% and Best Aver...
For the external-anchor test equating model, two observed-score methods are derived using the slope...
Results for the group 0 v group 2 balanced data set (Best Average Test Performance = 78.8% Best Aver...
Existing procedures for testing measurement invariance focus mainly on group-level comparisons rathe...
The applied statistician often encounters the need to compare two or more groups with respect to mor...