regression • censored outcomes • endogenous regressors • bootstrap, jackknife, and robust and cluster–robust variance • instrumental variables • three-stage least squares • constraints • quantile regression • GLS • more random and fixed effects with robust standard errors • linear mixed models • random-effects probit • GEE • random- and fixed-effects Poisson • dynamic panel-data models • instrumental variables • panel unit-root tests • more continuous, binary, count, and survival outcomes • two-, three-, and higher-level models • generalized linear models • random-intercepts • random-slopes • crossed random effects • BLUPs of effects and fitted values • hierarchical models • residual error structures • DDF adjustments • support for survey data • more logistic, probit, tobit • Poisson and negative binomial • conditional, multinomial, nested, ordered, rank-ordered, and stereotype logistic • multinomial probit • zero-inflated and left-truncated count models • selection models • marginal effects • more Wald tests • LR tests • linear and nonlinear combinations • predictions and generalized predictions • marginal means • least-squares means • adjusted means • marginal and partial effects • forecast models • Hausman tests • more compare means, intercepts, or slopes • compare to reference category, adjacent category, grand mean, etc. Performs a joint test for the addition of the specified variables to the last model, the results of which may be retrieved using the accessors $test and $pvalue.The method requires that a certain number of moment conditions were specified for the model.These moment conditions are functions of the model parameters and the data, such that their expectation is zero at the true values of the parameters.Menu path: Model window, /Tests/Add variables command with regular time series data.

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