What every test returns¶

Source: man/test_results.Rd · Help: ?test_results

Every exported perform*Test() function returns a base-R htest object, so a result prints, subsets and composes like the result of stats::t.test() or lmtest::bptest(). This page lists every field such a result can hold: the five every test returns, the two optional htest fields some return, and the fields a few tests add. tests/testthat/test-return-contract.R checks every exported test against it.

Fields of every test¶

statistic: the test statistic: a numeric value of length one, named after the statistic ("X-squared", "F", "t", "GQ", "LM", "z", ...).
parameter: the parameters of the null distribution: a numeric vector whose elements are named, usually degrees of freedom ("df", or "df1" and "df2"). The resampling tests store the number of replications here ("B", "permutations"), and the tests on ordered observations the sizes they use ("n", "m"). It is NULL for performPesaranTest(), whose statistic is referred to the standard normal distribution.
p.value: the p-value: a single number between 0 and 1.
method: a character string naming the test. When an argument switches between two statistics, such as studentize in performHarveyTest(), the string says which one was computed.
data.name: a character string describing what was tested: the formula of the model, followed for some tests by the variance regressors. For performBoxMTest(), which tests data rather than a model, it names the data and the grouping.

Optional htest fields¶

alternative: a character string describing the alternative hypothesis, returned by the tests that have a direction or a stated alternative.
estimate: estimates that accompany the statistic: a named numeric vector (performSzroeterTest(), performSpearmanTest(), performVarianceFormTest()), or, in performQuantileRegressionTest(), a matrix of slope estimates with one column per quantile and named rows and columns.

Fields some tests add¶

p.value_bootstrap: performWhiteTestRobust() and performBPTestRobust() with bootstrap = TRUE: the bootstrap p-value.
robust_details: performWhiteTestRobust() and performBPTestRobust(): a list with the confidence interval, effect size, bootstrap results, power and sample size, and method or studentized, the setting that chose the statistic.
boot_statistics: performWhiteTestBootstrap(): the bootstrap replicates of the statistic.
bootstrap: performWildBootstrapTest(): a list with the replicates, the number of usable ones, the multiplier distribution and the observed statistic.
permutation: performRankPermutationTest(): a list with the replicates, the number of usable ones and the ordering variable.
projection: performHighDimensionalTest(): a list with the number of principal components kept, the share of the variance they explain and the threshold that chose them.
variance_function: performVarianceFormTest(): a list with the form of the variance function, its regressors and the added terms that were tested.
quantiles, se_type, iid: performQuantileRegressionTest(): the quantiles compared and the settings of the standard errors.
chunks_processed, chunk_size, r_squared: performWhiteTestStreaming(), performBPTestStreaming() and performKoenkerTestStreaming(): how the data were read and the $R^2$ of the auxiliary regression.
res: performSpatialHeteroTest(): the Monte Carlo replicates of Moran's I from spdep::moran.mc(), whose class "mc.sim" the result keeps.

Attributes¶

performWhiteTest() and performWhiteTestRobust() attach the attributes auxiliary_regressors, original_regressors, cross_products_included and r_squared_auxiliary, which describe the auxiliary regression. runHeteroTests() adds attributes of its own to each result it returns.

Inputs every test refuses¶

Since 0.15.0 every test on a model refuses four inputs, each with one message: a glm that is not a least-squares fit, that is, of any family but gaussian or with any link but the identity ("needs a model fitted by stats::lm()"); a model with a coefficient that is not finite, such as the NA of an aliased term ("Model coefficients must be finite"); data that lack rows the model was fitted to; and data that lack a variable of the model ("The following variables are missing from"). The model frame is accepted as data as it is. A glm with the Gaussian family and the identity link is accepted and gives the result of the lm up to rounding error, except that performWhiteTestStreaming(), performHarrisonMcCabeTest() and performVarianceFormTest() refuse every glm. With positive prior weights it gives the result of lm(..., weights = w): performGQTest(), performRESETTest(), performWhiteTestBootstrap() and performWildBootstrapTest(), which read the weights of an lm, read the prior weights of the glm, and performQuantileRegressionTest(), which refuses a weighted lm, refuses it with the same message. A survey::svyglm() fit is refused by every test ("The model is a survey::svyglm() fit"). tests/testthat/test-input-validation.R gives every test these inputs.

The tests that read data also refuse data whose rows cannot be confirmed to hold the observations of the fit ("cannot match the rows of data to the observations of the model"). They match the rows of data to the residuals by row name, and a tibble, a data.table or a data frame whose row names were reset, as by dplyr::arrange(), has row names that only number its rows. Before a test reads data, the rows the row names pick are compared with the model frame of the fit, row by row: every column data holds under its own name, value by value, and the others (log(x), poly(x, 2), offset(o), the weights and an offset given as arguments) computed from data as the fit computed them. A term computed from the rows it is given, such as I(x - mean(x)), and a column that names a variable data does not hold, are not compared; for a term of variables of data, the compared columns must then tell the rows of the fit apart. Data that cannot be confirmed so are refused, even the data of the fit: when no column can be compared, as with lm(d$y ~ d$x), or when the compared columns tie on rows that differ in such a term. Pass the full data the model was fitted on, or the variables as columns of data. Data without row names of their own in another order than the fit, or with rows in front of those of the fit, are refused, as are repeated row names, and a model frame rebuilt for a fit with model = FALSE from data that changed after the fit. Data with row names of their own are matched by name, in any order, except by performPesaranTest(), performBPRandomEffectsTest() and performScatterDiagnostic(), which read data by position and need its rows in the order of the fit. tests/testthat/test-data-alignment-guard.R checks these refusals.