dist.plot: Graphical balance check for covariate distributions in...
In nonrandom: Stratification and matching by the propensity score

Description Usage Arguments Details Value Author(s) See Also Examples

Plot covariate disitribution in treatment groups

  dist.plot(object, sel=NULL, treat=NULL, stratum.index=NULL,
  match.index=NULL, plot.type=1, compare=FALSE, cat.levels=2,
  plot.levels=5, label.match=NULL, label.stratum=c("Stratum","Original"),
  with.legend=TRUE, legend.title=NULL, legend.cex=0.9, myoma=c(3,2,2,2),
  mymar=c(5,4,1,2), width=0.5, xlim=NULL, ylim=NULL, col=NULL, las=1,
  font.main=2, font=1, main=NULL, main.cex=1.2, sub.cex=0.9,
  bar.cex=0.8, ...)

`object`	an object of class 'pscore', 'stratified.pscore', 'stratified.data.frame', 'matched.pscore', 'matched.data.frame', 'matched.data.frames' or a data frame. If object class is 'pscore', arguments `stratum.index` or `match.index` are ignored.
`sel`	a data frame or a vector of integers or strings indicating covariates to be plotted. The default is 'NULL', i.e. the complete data set is selected.
`treat`	an integer or a string describing the treatment indicator in 'data' and 'data.matched', respectively, if `ps.match()` is previously used. If the class of the input object is 'stratified.pscore' or 'matched.pscore', no specification is needed.
`stratum.index`	an integer or a string indicating the vector containing the stratum indices in stratified data. No specification is needed if `ps.makestrata()` is previously used.
`match.index`	an integer or a string indicating the vector containing the matching indices in data and in the matched data. No specification is needed if `ps.match()` is previously used.
`plot.type`	an integer specifying the plot type. The default is '1', i.e. means for continuous and frequencies for categorical covariates are plotted as barplots separated by treatment. If `plot.type`='2', histograms are shown.
`compare`	a logical value indicating whether the covariate distribution in the original data are plotted.
`cat.levels`	an integer. The default is '2', i.e. covariates with more than two different values are considered as continuous.
`plot.levels`	an integer. The default is '5', i.e. five cutpoints are used to define histogram classes for continuous covariates. Caution: The classification depends on the data structure such that the class number used in the histogram may differ from the statement in `plot.levels`.
`label.match`	a vector of two strings describing the labels for the original and the matched data. The default is 'NULL', i.e. c('Original', 'Matched') is used.
`label.stratum`	a string describing the labels for the stratum-specific data.
`with.legend`	a logical value indicating whether a legend is shown.
`legend.title`	a string indicating the legend title. The default is 'NULL', i.e either covariate categories or treatment labels in case of continuous covariates are given if `plot.type`='1'. For `plot.type`='2', treatment labels are shown.
`legend.cex`	a numeric indicating the font size in the legend.
`myoma`	the size of outer margins, see `par`.
`mymar`	margins to be specified on the four sides of the plot, see `par`.
`width`	an integer indicating bar widths.
`xlim`	a vector of integers of length two indicating limits for the x axis.
`ylim`	a vector of integers of length two indicating limits for the y axis. It is only meaningful if `plot.type`='2'.
`col`	a vector of colors for bars or bar components. The vector length should depend on the `plot.type` and the category levels of the plotted covariates.
`las`	a integer indicating the style of axis labels, see `par`.
`font.main`	an integer indicating the font to be used for plot main titles, see `par`.
`font`	an integer specifying the font to use for text, see `par`.
`main`	a string indicating the main title for graphics.
`main.cex`	a numeric indicating the font size of main title.
`sub.cex`	a numeric indicating the font size of sub titles.
`bar.cex`	a numeric indicating the font size of bar titles.
`...`	further arguments for graphics.

Propensity score methods aims to eliminate imbalances in covariate distributions between treatment groups. An important issue is to check those after stratification or matching.

The usage of dist.plot() depends on the class of the input object. If either ps.makestrata() or ps.match() are previously used, treat, match.index and stratum.index are not needed, contrary to the case where the input object is a data frame.

dist.plot() returns a list containing information for graphics. The number and the manner of the list entries depends on plot.type and on the type of covariates to be plotted:

`name.sel`	a string containing names of the selected covariates.
`sel`	a data frame containing the selected covariates labeled by 'name.sel'.
`name.treat`	a string indicating the name of the selected treatment variable.
`treat`	a vector containing the treatment variable labeled by 'name.treat'.
`name.stratum.index`	a string indicating the name of the selected stratum indices.
`stratum.index`	a vector containing the stratum variable labeled by 'name.stratum.index'.
`name.match.index`	a string indicating the name of the selected matching indices.
`match.index`	a vector containing the matching variable labeled by 'name.match.index'.
`var.cat`	a string indicating the names of categorical variables.
`var.noncat`	a string indicating the names of continuous variables.
`mean`	a list of length two including means of continuous covariates separated by treatment. If `compare`='FALSE', list elements are matrices with means separated by treatment (rows) and strata or matched/unmatched data (columns), respectively. If `compare`='TRUE', the list elements are lists including means before (first list element) and after (second list element) stratification or matching. The order of list elements is in accordance to the order of 'var.noncat'. It is only available if `plot.type`=1.
`frequency`	a list with length according to the number of categorical covariates whereas the list elements depend on `compare`. If `compare`='FALSE', list elements contain standardized frequency tables separated by treatment (rows) and by strata or by matched/unmatched data (columns). The order and the number of list elements is w.r.t. 'var.cat'. If `compare`='TRUE', there are two list elements which are lists of frequency tables. The first list element contains lists of frequency tables separated by treatment before stratification or matching and the second list element includes lists of frequency tables separated by treatment and strata or matched/unmatched data. The order of list elements is in accordance to the order of 'var.cat'. It is only available if `plot.type`=1.
`breaks.noncat`	a list with length according to the number of continuous covariates. The list entries are numerics indicating the cutpoints of histogram classes. It is only available if `plot.type`=2.
`x.cat`	a list with length according to the number of categorical covariates. It contains frequencies w.r.t. treatment with the lower value, e.g., '0' or 'No', before stratification or matching. It is only available if `plot.type`=2 and `compare`='TRUE'.
`y.cat`	a list with length according to the number of categorical covariates. It contains frequencies w.r.t. treatment with the upper value, e.g., '1' or 'Yes', before stratification or matching. It is only available if `plot.type`=2 and `compare`='TRUE'.
`x.s.cat`	a list with length according to the number of categorical covariates. It contains frequencies w.r.t. strata (columns) and treatment with the lower value, e.g., '0' or 'No' after stratification. If `match.index` is used, frequencies are given w.r.t. treatment with the lower value and w.r.t. the original data (first column) and the matched data (second column). It is only available if `plot.type`=2.
`y.s.cat`	a list with length according to the number of categorical covariates. It contains frequencies w.r.t. strata (columns) and treatment with the upper value, e.g., '1' or 'Yes' after stratification. If `match.index` is used, frequencies are given w.r.t. treatment with the upper value and w.r.t. the original data (first column) and the matched data (second column). It is only available if `plot.type`=2.
`x.noncat`	a list with length according to the number of continuous covariates. It contains frequencies in histogram classes w.r.t. treatment with the lower value, e.g., '0' or 'No', before stratification or matching. It is only available if `plot.type`=2 and `compare`='TRUE'.
`y.noncat`	a list with length according to the number of continuous covariates. It contains frequencies in histogram classes w.r.t. treatment with the upper value, e.g., '1' or 'Yes', before stratification or matching. It is only available if `plot.type`=2 and `compare`='TRUE'.
`x.s.noncat`	a list with length according to number of continuous covariates. It contains lists with frequencies in histogram classes w.r.t. strata and treatment with the lower value, e.g., '0' or 'No', after stratification. If `match.index` is used, frequencies in histogram classes are given w.r.t. treatment with the lower value and w.r.t. the original data and the matched dats. It is only available if `plot.type`=2.
`y.s.noncat`	a list with length according to number of continuous covariates. It contains lists with frequencies in histogram classes w.r.t. strata and treatment with the upper value, e.g., '1' or 'Yes', after stratification. If `match.index` is used, frequencies in histogram classes are given w.r.t. treatment with the upper value and w.r.t. the original data and the matched dats. It is only available if `plot.type`=2.

Susanne Stampf susanne.stampf@usb.ch

barplot

## STU1
data(stu1)
stu1.ps <- pscore(data    = stu1, 
                  formula = therapie~tgr+age)
stu1.match <- ps.match(object          = stu1.ps,
                       ratio           = 2,
                       caliper         = 0.5,
                       givenTmatchingC = FALSE,
                       matched.by      = "pscore",
                       setseed         = 38902)
stu1.plot <- 
    dist.plot(object      = stu1.match, 
              sel         = c("age"),
              compare     = TRUE,
              plot.type   = 2,
              with.legend = FALSE)

## PRIDE
data(pride)
pride.ps <- pscore(data        = pride,
                   formula     = PCR_RSV~SEX+RSVINF+REGION+
                                 AGE+ELTATOP+EINZ+EXT,
                   name.pscore = "ps")
pride.strata <- ps.makestrata(object = pride.ps,
                              breaks = quantile(pride.ps$pscore,  
                                                seq(0,1,0.2)),
                              stratified.ps = "ps")
pride.plot <- 
   dist.plot(object    = pride.strata,      
             sel       = c("REGION", "AGE"),
             plot.type = 1)                  ## default