#Bal cobalt login full

This can also be used with a binary treatment to assess balance with respect to the full sample. Whether balance should be computed for pairs of treatments or for each treatment against all groups combined. See for details.Įither a vector containing imputation indices for each unit or a string containing the name of the imputation index variable in data or the original data set used in the call to ps(), mnps(), iptw(), or ps.cont(). Each entry can be a vector of weights, the name of a variable in data that contains weights, or an object with a get.w() method.Įither a vector containing cluster membership for each unit or a string containing the name of the cluster membership variable in data or the ps, mnps, iptw, or ps.cont object. See Details.Ī named list containing additional weights on which to assess balance. Requesting a threshold automatically requests the display of that statistic. For example, to request thresholds on mean differences and variance ratios, one can set thresholds = c(m =. Abbreviations allowed.Ī named vector of balance thresholds, where the name corresponds to the statistic (i.e., in stats) that the threshold applies to. Use 'all' to get the same values computed by bal.table in twang. If not specified, for ps objects, bal.tab() will use 'treated' if the estimand of the call to ps() is the ATT and 'pooled' if the estimand is the ATE for mnps objects, bal.tab() will use 'treated' if treatATT was specified in the original call to mnps and 'pooled' otherwise. This argument is used to set std in col_w_smd() and col_w_corr.Ĭharacter how the denominator for standardized mean differences should be calculated, if requested. This option can be set globally using (). Whether mean differences for binary covariates (i.e., difference in proportion) should be standardized ( 'std') or raw ( 'raw'). This argument is used to set std in col_w_smd() and col_w_corr. Whether mean differences for continuous covariates should be standardized ( 'std') or raw ( 'raw'). In this case, imp is automatically supplied using the imputation variable created from processing the mids object. Can also be mids object, the output of a call to mice() from the mice package, containing multiply imputed data sets. For iptw objects, can be a list of additional covariate values as described above, with one list entry per time period.Īn optional data frame containing variables that might be named in arguments to distance, addl, cluster, and imp. If a formula or variable names are specified, bal.tab() will look first in the argument to data, if specified, and next in the input object. Note that the propensity scores generated by ps() and iptw() (but not mnps() or ps.cont()) are automatically included and named ''.Īn optional formula or data frame containing additional covariates for which to present balance or a character vector containing their names. If a formula or variable names are specified, bal.tab() will look in the argument to data, if specified. If int is numeric, poly will take on the value of int.Īn optional formula or data frame containing distance values (e.g., propensity scores) or a character vector containing their names. If 1, the default, only the base covariate will be displayed. For example, if 2, squares of each continuous covariate will be displayed (in addition to the covariate itself) if 3, squares and cubes of each continuous covariate will be displayed, etc. Numeric the highest polynomial of each continuous covariate to display. If numeric, will be passed to poly as well. Logical or numeric whether or not to include 2-way interactions of covariates included in covs and in addl. For continuous treatments, 'correlations' (i.e., treatment-covariate Pearson correlations) is the default. For binary and multi-category treatments, 'mean.diffs' (i.e., mean differences) is the default. If no stopping methods are provided, bal.tab will default to displaying balance for all available stopping methods.Ĭharacter which statistic(s) should be reported. The names can be abbreviated as long as the abbreviations are specific enough.

bal.tab will assess balance for the weights created by those stopping methods. Examples include 'es.max' or 'ks.mean' for ps and mnps objects and 'p.mean' or 's.max' for ps.cont objects.

A ps, mnps, iptw, or ps.cont object the output of a call to twang::ps(), twang::mnps(), twang::iptw() or WeightIt::ps.cont().Ī string containing the names of the stopping methods used in the original call to ps(), mnps(), iptw(), or ps.cont().

Bal cobalt login