{"method":"tidy","column":"acf","description":"Autocorrelation."}
{"method":"tidy","column":"adj.p.value","description":"P-value adjusted for multiple comparisons."}
{"method":"tidy","column":"alternative","description":"Alternative hypothesis (character)."}
{"method":"tidy","column":"at.value","description":"Value(s) used to calculate AMEs."}
{"method":"tidy","column":"at.variable","description":"Variable(s) used to calculate average marginal effects (AMEs)."}
{"method":"tidy","column":"atmean","description":"Marginal effects were calculated as either partial effects for the mean observation (TRUE), or as mean partial effects (FALSE)."}
{"method":"tidy","column":"autocorrelation","description":"Autocorrelation."}
{"method":"tidy","column":"bias","description":"Bias of the statistic."}
{"method":"tidy","column":"ci.width","description":"Expected width of confidence interval."}
{"method":"tidy","column":"class","description":"The class under consideration."}
{"method":"tidy","column":"cluster","description":"A factor describing the cluster from 1:k."}
{"method":"tidy","column":"coef.type","description":"Type of coefficient."}
{"method":"tidy","column":"column1","description":"Name or index of the first column being described."}
{"method":"tidy","column":"column2","description":"Name or index of the second column being described."}
{"method":"tidy","column":"comp","description":"ID of the model component."}
{"method":"tidy","column":"comparison","description":"Levels being compared."}
{"method":"tidy","column":"component","description":"ID of the cluster or component being considered."}
{"method":"tidy","column":"conf.high","description":"Upper bound on the confidence interval for the estimate."}
{"method":"tidy","column":"conf.low","description":"Lower bound on the confidence interval for the estimate."}
{"method":"tidy","column":"contrast","description":"Levels being compared."}
{"method":"tidy","column":"cumulative","description":"Cumulative percentage of variation explained."}
{"method":"tidy","column":"cutoff","description":"The cutoff used for classification. Observations with predicted probabilities above this value were assigned class 1, and observations with predicted probabilities below this value were assigned class 0."}
{"method":"tidy","column":"delta","description":"True difference in means."}
{"method":"tidy","column":"den.df","description":"Degrees of freedom of the denominator."}
{"method":"tidy","column":"denominator","description":"The denominator, which is tau=kendall_score/denominator."}
{"method":"tidy","column":"dev.ratio","description":"Fraction of null deviance explained at each value of lambda."}
{"method":"tidy","column":"df","description":"Degrees of freedom used by this term in the model."}
{"method":"tidy","column":"distance","description":"Distance between items."}
{"method":"tidy","column":"estimate","description":"The estimated value of the regression term."}
{"method":"tidy","column":"estimate1","description":"Sometimes two estimates are computed, such as in a two-sample t-test."}
{"method":"tidy","column":"estimate2","description":"Sometimes two estimates are computed, such as in a two-sample t-test."}
{"method":"tidy","column":"event","description":"Observed number of events."}
{"method":"tidy","column":"exp","description":"Weighted expected number of events in each group."}
{"method":"tidy","column":"expected","description":"Expected number of events."}
{"method":"tidy","column":"fpr","description":"False positive rate."}
{"method":"tidy","column":"freq","description":"Vector of frequencies at which the spectral density is estimated."}
{"method":"tidy","column":"GCV","description":"Generalized cross validation error estimate."}
{"method":"tidy","column":"group","description":"The group (if specified) in the lavaan model."}
{"method":"tidy","column":"group1","description":"First group being compared."}
{"method":"tidy","column":"group2","description":"Second group being compared."}
{"method":"tidy","column":"index","description":"Index (i.e. date or time) for a `ts` or `zoo` object."}
{"method":"tidy","column":"item1","description":"First item."}
{"method":"tidy","column":"item2","description":"Second item."}
{"method":"tidy","column":"kendall_score","description":"Kendall score."}
{"method":"tidy","column":"lag","description":"Lag values."}
{"method":"tidy","column":"lambda","description":"Value of penalty parameter lambda."}
{"method":"tidy","column":"letters","description":"Compact letter display denoting all pair-wise comparisons."}
{"method":"tidy","column":"lhs","description":"Left hand side."}
{"method":"tidy","column":"logLik","description":"Log-likelihood at the fitted value of the parameters."}
{"method":"tidy","column":"mcmc.error","description":"The MCMC error."}
{"method":"tidy","column":"mean","description":"The mean for each component. In case of 2+ dimensional models, a column with the mean is added for each dimension. NA for noise component."}
{"method":"tidy","column":"meansq","description":"Mean sum of squares. Equal to total sum of squares divided by degrees of freedom."}
{"method":"tidy","column":"method","description":"Method used."}
{"method":"tidy","column":"n","description":"Number of observations by component."}
{"method":"tidy","column":"N","description":"Number of subjects in each group."}
{"method":"tidy","column":"n.censor","description":"Number of censored events."}
{"method":"tidy","column":"n.event","description":"Number of events at time t."}
{"method":"tidy","column":"n.risk","description":"Number of individuals at risk at time zero."}
{"method":"tidy","column":"null.value","description":"Value to which the estimate is compared."}
{"method":"tidy","column":"num.df","description":"Degrees of freedom."}
{"method":"tidy","column":"nzero","description":"Number of non-zero coefficients for the given lambda."}
{"method":"tidy","column":"obs","description":"weighted observed number of events in each group."}
{"method":"tidy","column":"op","description":"The operator in the model syntax (e.g. `~~` for covariances, or `~` for regression parameters)."}
{"method":"tidy","column":"outcome","description":"Outcome of manifest variable."}
{"method":"tidy","column":"p","description":"True proportion."}
{"method":"tidy","column":"p.value","description":"The two-sided p-value associated with the observed statistic."}
{"method":"tidy","column":"p.value.Sargan","description":"p-value for Sargan test of overidentifying restrictions."}
{"method":"tidy","column":"p.value.weakinst","description":"p-value for weak instruments test."}
{"method":"tidy","column":"p.value.Wu.Hausman","description":"p-value for Wu-Hausman weak instruments test for endogeneity."}
{"method":"tidy","column":"parameter","description":"The parameter being modeled."}
{"method":"tidy","column":"PC","description":"An integer vector indicating the principal component."}
{"method":"tidy","column":"percent","description":"Percentage of variation explained."}
{"method":"tidy","column":"power","description":"Power achieved for given value of n."}
{"method":"tidy","column":"proportion","description":"The mixing proportion of each component"}
{"method":"tidy","column":"pyears","description":"Person-years of exposure."}
{"method":"tidy","column":"response","description":"Which response column the coefficients correspond to (typically `Y1`, `Y2`, etc)."}
{"method":"tidy","column":"rhs","description":"Right hand side."}
{"method":"tidy","column":"robust.se","description":"robust version of standard error estimate."}
{"method":"tidy","column":"row","description":"Row ID of the original observation."}
{"method":"tidy","column":"scale","description":"Scaling factor of estimated coefficient."}
{"method":"tidy","column":"sd","description":"Standard deviation."}
{"method":"tidy","column":"series","description":"Name of the series (present only for multivariate time series)."}
{"method":"tidy","column":"sig.level","description":"Significance level (Type I error probability)."}
{"method":"tidy","column":"size","description":"Number of points assigned to cluster."}
{"method":"tidy","column":"spec","description":"Vector (for univariate series) or matrix (for multivariate series) of estimates of the spectral density at frequencies corresponding to freq."}
{"method":"tidy","column":"state","description":"State (if multistate survfit object inputted)."}
{"method":"tidy","column":"statistic","description":"The value of a T-statistic to use in a hypothesis that the regression term is non-zero."}
{"method":"tidy","column":"statistic.Sargan","description":"Statistic for Sargan test of overidentifying restrictions."}
{"method":"tidy","column":"statistic.weakinst","description":"Statistic for Wu-Hausman test."}
{"method":"tidy","column":"statistic.Wu.Hausman","description":"Statistic for Wu-Hausman weak instruments test for endogeneity."}
{"method":"tidy","column":"std_estimate","description":"The standardized regression coefficients."}
{"method":"tidy","column":"std.all","description":"Standardized estimates based on both the variances of both (continuous) observed and latent variables."}
{"method":"tidy","column":"std.dev","description":"Standard deviation explained by this PC."}
{"method":"tidy","column":"std.error","description":"The standard error of the regression term."}
{"method":"tidy","column":"std.lv","description":"Standardized estimates based on the variances of the (continuous) latent variables only."}
{"method":"tidy","column":"std.nox","description":"Standardized estimates based on both the variances of both (continuous) observed and latent variables, but not the variances of exogenous covariates."}
{"method":"tidy","column":"step","description":"Which step of lambda choices was used."}
{"method":"tidy","column":"strata","description":"Strata if stratified survfit object inputted."}
{"method":"tidy","column":"stratum","description":"The error stratum."}
{"method":"tidy","column":"study","description":"The estimate type (summary vs individual study)."}
{"method":"tidy","column":"sumsq","description":"Sum of squares explained by this term."}
{"method":"tidy","column":"tau","description":"Quantile."}
{"method":"tidy","column":"term","description":"The name of the regression term."}
{"method":"tidy","column":"time","description":"Point in time."}
{"method":"tidy","column":"tpr","description":"The true positive rate at the given cutoff."}
{"method":"tidy","column":"type","description":"Either \"weighted\" or \"unweighted\"."}
{"method":"tidy","column":"uniqueness","description":"Proportion of residual, or unexplained variance."}
{"method":"tidy","column":"value","description":"The value/estimate of the component. Results from data reshaping."}
{"method":"tidy","column":"var_kendall_score","description":"Variance of the kendall_score."}
{"method":"tidy","column":"variable","description":"Variable under consideration."}
{"method":"tidy","column":"variance","description":"In case of one-dimensional and spherical models, the variance for each component, omitted otherwise. `NA` for noise component."}
{"method":"tidy","column":"withinss","description":"The within-cluster sum of squares."}
{"method":"tidy","column":"y.level","description":"The response level."}
{"method":"tidy","column":"y.value","description":"The response level."}
{"method":"tidy","column":"z","description":"z score."}
{"method":"glance","column":"adj.r.squared","description":"Adjusted R squared statistic, which is like the R squared statistic except taking degrees of freedom into account."}
{"method":"glance","column":"agfi","description":"Adjusted goodness of fit."}
{"method":"glance","column":"AIC","description":"Akaike's Information Criterion for the model."}
{"method":"glance","column":"AICc","description":"Small sample corrected Akaike's Information Criterion for the model."}
{"method":"glance","column":"alpha","description":"Estimated correlation parameter for geepack::geeglm."}
{"method":"glance","column":"alternative","description":"The alternative hypothesis. Usually character."}
{"method":"glance","column":"autocorrelation","description":"Autocorrelation."}
{"method":"glance","column":"avg.silhouette.width","description":"The average silhouette width for the dataset."}
{"method":"glance","column":"betweenss","description":"The total between-cluster sum of squares."}
{"method":"glance","column":"BIC","description":"Bayesian Information Criterion for the model."}
{"method":"glance","column":"cfi","description":"Comparative fit index."}
{"method":"glance","column":"chi.squared","description":"The Pearson Chi-Square goodness of fit statistic for multiway tables."}
{"method":"glance","column":"chisq","description":"Model chi squared."}
{"method":"glance","column":"cochran.qe","description":"In meta-analysis, test statistic for the Cochran's Q_e test of residual heterogeneity."}
{"method":"glance","column":"cochran.qm","description":"In meta-analysis, test statistic for the Cochran's Q_m omnibus test of coefficients."}
{"method":"glance","column":"conf.high","description":"Upper bound on confidence interval."}
{"method":"glance","column":"conf.low","description":"Lower bound on confidence interval."}
{"method":"glance","column":"converged","description":"Logical indicating if the model fitting procedure was succesful and converged."}
{"method":"glance","column":"convergence","description":"Convergence code."}
{"method":"glance","column":"crit","description":"Minimized criterion"}
{"method":"glance","column":"cv.crit","description":"Cross-validation score"}
{"method":"glance","column":"den.df","description":"Degrees of freedom of the denominator"}
{"method":"glance","column":"deviance","description":"Deviance of the model."}
{"method":"glance","column":"df","description":"Degrees of freedom used by the model."}
{"method":"glance","column":"df.null","description":"Degrees of freedom used by the null model."}
{"method":"glance","column":"df.residual","description":"Residual degrees of freedom."}
{"method":"glance","column":"dw.original","description":"Durbin-Watson statistic of original fit."}
{"method":"glance","column":"dw.transformed","description":"Durbin-Watson statistic of transformed fit."}
{"method":"glance","column":"edf","description":"The effective degrees of freedom."}
{"method":"glance","column":"estimator","description":"Estimator used."}
{"method":"glance","column":"events","description":"Number of events."}
{"method":"glance","column":"finTol","description":"The achieved convergence tolerance."}
{"method":"glance","column":"function.count","description":"Number of calls to `fn`."}
{"method":"glance","column":"G","description":"The optimal number of mixture components."}
{"method":"glance","column":"g.squared","description":"The likelihood ratio/deviance statistic."}
{"method":"glance","column":"gamma","description":"Estimated scale parameter for geepack::geeglm."}
{"method":"glance","column":"gradient.count","description":"Number of calls to `gr`."}
{"method":"glance","column":"H","description":"H statistic for computing confidence interval of major axis slope."}
{"method":"glance","column":"h.squared","description":"Value of the H-Squared statistic."}
{"method":"glance","column":"hypvol","description":"If the other model contains a noise component, the value of the hypervolume parameter. Otherwise `NA`."}
{"method":"glance","column":"i.squared","description":"Value of the I-Squared statistic."}
{"method":"glance","column":"independence","description":"Whether the model assumed dyadic independence."}
{"method":"glance","column":"isConv","description":"Whether the fit successfully converged."}
{"method":"glance","column":"iter","description":"Iterations of algorithm/fitting procedure completed."}
{"method":"glance","column":"iterations","description":"The number of iterations performed before convergence."}
{"method":"glance","column":"kHKB","description":"Modified HKB estimate of the ridge constant."}
{"method":"glance","column":"kLW","description":"Modified L-W estimate of the ridge constant."}
{"method":"glance","column":"lag.order","description":"Lag order."}
{"method":"glance","column":"lambda","description":"Choice of lambda corresponding to `spar`."}
{"method":"glance","column":"lambda.1se","description":"The value of the penalization parameter lambda that results in the sparsest model while remaining within one standard error of the minimum loss."}
{"method":"glance","column":"lambda.min","description":"The value of the penalization parameter lambda that achieved minimum loss as estimated by cross validation."}
{"method":"glance","column":"lambdaGCV","description":"choice of lambda that minimizes GCV."}
{"method":"glance","column":"logLik","description":"The log-likelihood of the model. [stats::logLik()] may be a useful reference."}
{"method":"glance","column":"max.cluster.size","description":"Max number of elements in clusters."}
{"method":"glance","column":"max.hazard","description":"Maximal estimated hazard."}
{"method":"glance","column":"max.time","description":"The maximum observed event or censoring time."}
{"method":"glance","column":"maxit","description":"Number of iterations performed."}
{"method":"glance","column":"MCMC.burnin","description":"The burn-in period of the MCMC estimation."}
{"method":"glance","column":"MCMC.interval","description":"The interval used during MCMC estimation."}
{"method":"glance","column":"MCMC.samplesize","description":"The sample size used during MCMC estimation."}
{"method":"glance","column":"measure","description":"The measure used in the meta-analysis."}
{"method":"glance","column":"median","description":"median survival."}
{"method":"glance","column":"method","description":"Which method was used."}
{"method":"glance","column":"min.hazard","description":"Minimal estimated hazard."}
{"method":"glance","column":"min.time","description":"The minimum observed event or censoring time."}
{"method":"glance","column":"missing_method","description":"Method for eliminating missing data."}
{"method":"glance","column":"model","description":"A character string denoting the model at which the optimal BIC occurs."}
{"method":"glance","column":"n","description":"The total number of observations."}
{"method":"glance","column":"n.clusters","description":"Number of clusters."}
{"method":"glance","column":"n.factors","description":"The number of fitted factors."}
{"method":"glance","column":"n.max","description":"Maximum number of subjects at risk."}
{"method":"glance","column":"n.start","description":"Initial number of subjects at risk."}
{"method":"glance","column":"nevent","description":"Number of events."}
{"method":"glance","column":"nexcluded","description":"Number of excluded observations."}
{"method":"glance","column":"ngroups","description":"Number of groups in model."}
{"method":"glance","column":"nobs","description":"Number of observations used."}
{"method":"glance","column":"norig","description":"Number of observation in the original dataset."}
{"method":"glance","column":"npar","description":"Number of parameters in the model."}
{"method":"glance","column":"npasses","description":"Total passes over the data across all lambda values."}
{"method":"glance","column":"null.deviance","description":"Deviance of the null model."}
{"method":"glance","column":"nulldev","description":"Null deviance."}
{"method":"glance","column":"num.df","description":"Degrees of freedom of the numerator."}
{"method":"glance","column":"number.interaction","description":"Number of interactions."}
{"method":"glance","column":"offtable","description":"Total number of person-years off table."}
{"method":"glance","column":"p.value","description":"P-value corresponding to the test statistic."}
{"method":"glance","column":"p.value.cochran.qe","description":"In meta-analysis, p-value for the Cochran's Q_e test of residual heterogeneity."}
{"method":"glance","column":"p.value.cochran.qm","description":"In meta-analysis, p-value for the Cochran's Q_m omnibus test of coefficients."}
{"method":"glance","column":"p.value.original","description":"P-value of original Durbin-Watson statistic."}
{"method":"glance","column":"p.value.Sargan","description":"P-value for Sargan test."}
{"method":"glance","column":"p.value.transformed","description":"P-value of autocorrelation after transformation."}
{"method":"glance","column":"p.value.weak.instr","description":"P-value for weak instrument F-test."}
{"method":"glance","column":"p.value.Wu.Hausman","description":"P-value for Wu-Hausman test."}
{"method":"glance","column":"parameter","description":"Parameter field in the htest, typically degrees of freedom."}
{"method":"glance","column":"pen.crit","description":"Penalized criterion."}
{"method":"glance","column":"power","description":"Power achieved by the analysis."}
{"method":"glance","column":"power.reached","description":"Whether the desired power was reached."}
{"method":"glance","column":"pseudo.r.squared","description":"Like the R squared statistic, but for situations when the R squared statistic isn't defined."}
{"method":"glance","column":"r.squared","description":"R squared statistic, or the percent of variation explained by the model. Also known as the coefficient of determination."}
{"method":"glance","column":"records","description":"Number of observations"}
{"method":"glance","column":"residual.deviance","description":"The residual deviance of the model"}
{"method":"glance","column":"rho","description":"Spearman's rho autocorrelation"}
{"method":"glance","column":"rho2","description":"McFadden's rho squared with respect to a market shares (constants-only) model."}
{"method":"glance","column":"rho20","description":"McFadden's rho squared with respect to an equal shares (no information) model."}
{"method":"glance","column":"rmean","description":"Restricted mean (see [survival::print.survfit()])."}
{"method":"glance","column":"rmean.std.error","description":"Restricted mean standard error."}
{"method":"glance","column":"rmsea","description":"Root mean square error of approximation."}
{"method":"glance","column":"rmsea.conf.high","description":"95 percent upper bound on RMSEA."}
{"method":"glance","column":"rscore","description":"Robust log-rank statistic"}
{"method":"glance","column":"score","description":"Score."}
{"method":"glance","column":"sigma","description":"Estimated standard error of the residuals."}
{"method":"glance","column":"sigma2_j","description":"The square root of the estimated residual variance for the j-th longitudinal process."}
{"method":"glance","column":"spar","description":"Smoothing parameter."}
{"method":"glance","column":"srmr","description":"Standardised root mean residual."}
{"method":"glance","column":"statistic","description":"Test statistic."}
{"method":"glance","column":"statistic.Sargan","description":"Statistic for Sargan test."}
{"method":"glance","column":"statistic.weak.instr","description":"Statistic for weak instrument F-test."}
{"method":"glance","column":"statistic.Wu.Hausman","description":"Statistic for Wu-Hausman test."}
{"method":"glance","column":"tau","description":"Quantile."}
{"method":"glance","column":"tau.squared","description":"In meta-analysis, estimated amount of residual heterogeneity."}
{"method":"glance","column":"tau.squared.se","description":"In meta-analysis, standard error of residual heterogeneity."}
{"method":"glance","column":"theta","description":"Angle between OLS lines `lm(y ~ x)` and `lm(x ~ y)`."}
{"method":"glance","column":"timepoints","description":"Number of timepoints."}
{"method":"glance","column":"tli","description":"Tucker Lewis index."}
{"method":"glance","column":"tot.withinss","description":"The total within-cluster sum of squares."}
{"method":"glance","column":"total","description":"Total number of person-years tabulated."}
{"method":"glance","column":"total.variance","description":"Total cumulative proportion of variance accounted for by all factors."}
{"method":"glance","column":"totss","description":"The total sum of squares."}
{"method":"glance","column":"value","description":"Minimized or maximized output value."}
{"method":"glance","column":"within.r.squared","description":"R squared within fixed-effect groups."}
{"method":"augment","column":".class","description":"Predicted class."}
{"method":"augment","column":".cluster","description":"Cluster assignment."}
{"method":"augment","column":".cochran.qe.loo","description":"Leave-one-out residual heterogeneity test statistics."}
{"method":"augment","column":".col.prop","description":"Column proportion (2 dimensional table only)."}
{"method":"augment","column":".conf.high","description":"Upper bound on confidence interval for fitted values."}
{"method":"augment","column":".conf.low","description":"Lower bound on confidence interval for fitted values."}
{"method":"augment","column":".cooksd","description":"Cooks distance."}
{"method":"augment","column":".cov.ratio","description":"The covariance ratio."}
{"method":"augment","column":".cred.high","description":"Upper bound on credible interval for fitted values."}
{"method":"augment","column":".cred.low","description":"Lower bound on credible interval for fitted values."}
{"method":"augment","column":".dffits","description":"Estimated change in standard deviations for the predicted effect after excluding the study"}
{"method":"augment","column":".expected","description":"Expected count under the null hypothesis."}
{"method":"augment","column":".fitted","description":"Fitted or predicted value."}
{"method":"augment","column":".fitted_j_0","description":"Population-level fitted values for the j-th longitudinal process."}
{"method":"augment","column":".fitted_j_1","description":"Individual-level fitted values for the j-th longitudinal process."}
{"method":"augment","column":".hat","description":"Diagonal of the hat matrix."}
{"method":"augment","column":".lower","description":"Lower bound on interval for fitted values."}
{"method":"augment","column":".moderator","description":"In meta-analysis, the moderators used to calculate the predicted values."}
{"method":"augment","column":".moderator.level","description":"In meta-analysis, the level of the moderators used to calculate the predicted values."}
{"method":"augment","column":".observed","description":"Observed count."}
{"method":"augment","column":".probability","description":"Class probability of modal class."}
{"method":"augment","column":".prop","description":"Proportion of the total."}
{"method":"augment","column":".remainder","description":"The remainder, or random, component of the decomposition."}
{"method":"augment","column":".resid","description":"The difference between observed and fitted values."}
{"method":"augment","column":".resid_j_0","description":"Population-level residuals for the j-th longitudinal process."}
{"method":"augment","column":".resid_j_1","description":"Individual-level residuals for the j-th longitudinal process."}
{"method":"augment","column":".row.prop","description":"Row proportion (2 dimensions table only)."}
{"method":"augment","column":".rownames","description":"Rownames from the original data, if present."}
{"method":"augment","column":".se.fit","description":"Standard errors of fitted values."}
{"method":"augment","column":".seasadj","description":"The seasonally adjusted (or *deseasonalised*) series."}
{"method":"augment","column":".seasonal","description":"The seasonal component of the decomposition."}
{"method":"augment","column":".sigma","description":"Estimated residual standard deviation when corresponding observation is dropped from model."}
{"method":"augment","column":".std.resid","description":"Standardised residuals."}
{"method":"augment","column":".tau","description":"Quantile."}
{"method":"augment","column":".tau.squared.loo","description":"leave-one-out tau-squared estimates"}
{"method":"augment","column":".trend","description":"The trend component of the decomposition."}
{"method":"augment","column":".uncertainty","description":"The uncertainty associated with the classification. Equal to one minus the model class probability."}
{"method":"augment","column":".upper","description":"Upper bound on interval for fitted values."}
{"method":"augment","column":".weight","description":"The final robust weights."}