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What does the Wald test do?
The Wald test (also called the Wald Chi-Squared Test) is a way to find out if explanatory variables in a model are significant. If the Wald test shows that the parameters for certain explanatory variables are zero, you can remove the variables from the model.
For what kind of testing problems are Wald tests used?
Wald test can be used to test the association between the independent variables (predictors) and the criterion variable (dependent) variable. A Wald test can be used in a great variety of different models including models for dichotomous variables and models for continuous variables.
Are t test and one-way ANOVA both Wald tests?
Are t test and one-way ANOVA both Wald tests? t-test for testing whether the mean of a normally distributed sample equals a constant is said to be a Wald test, by estimating the standard deviation of the sample mean by the fisher’s information of the normal distribution at the sample mean.
Why are Type III SS values different from estimate p-values?
The Type III SS section tests the overall effect of some_col while the Estimate section tests the simple effect of some_col when mealcat is at the level of the reference group. To make this clear, we can look at the SAS code that reproduces the Type III SS test using the estimate statement:
How are p-values used to test fixed effects?
For tests of fixed effects the p-values will be smaller. Thus if a p-value is greater than the cutoff value, you can be confident that a more accurate test would also retain the null hypothesis.
Which is better a parametric bootstrap or a p-value?
If the p-value was inconclusive, a parametric bootstrap could be used to provide a better estimated p-value. The p-value from the Wald test in the summary of the gmm model is 0.0939. This is about 20% larger than the 0.0783, p-value from the LRT.