# Caterpillar plot. Useful for plotting random effects from hierarchical models, such as MCMCglmm::MCMCglmm() object, that have binary outcome. ```r caterpillar_plot( subjID, subjLabel = NULL, remove.text.subjID = FALSE, show.stats = TRUE, mcmcglmm_object, orig_dataset, binaryOutcomeVar, prob = NULL, title = NULL, no.title = FALSE, subtitle = NULL, ncol = NULL, fonts = NULL, columnTextWidth = NULL, break.label.summary = FALSE ) ``` ## Arguments - `subjID`: key identifier field for participant ID in data sets - `subjLabel`: text label field in dataset to replace key identifier field for participant ID with in plot (if provided) - `remove.text.subjID`: boolean indicating if non-numeric text should be removed from subjID in plot label. Note that this can only be used if there are non-duplicate participant IDs when non-numeric text is removed. Default is FALSE (if provided) - `show.stats`: boolean indicating if (n, events) summary output should be shown in subject label - `mcmcglmm_object`: MCMCglmm model output - `orig_dataset`: data frame supplied to MCMCglmm function - `binaryOutcomeVar`: name of binary variable (0,1) that denotes outcome in MCMCglmm model - `prob`: probability for highest posterior density interval, similar to a confidence interval. Default is 0.95 (if provided) - `title`: title of the plot. Overrides default title (if provided) - `no.title`: boolean that denotes if title should be outputted in plot. Default is TRUE (if provided) - `subtitle`: subtitle of the plot. Overrides default subtitle (if provided) - `ncol`: number of columns in plot. Default is 2 (if provided) - `fonts`: character text that denotes font for title, subtitle, category labels, x-axis plot labels (if provided) - `columnTextWidth`: numeric that denotes character width for label text before breaking to start new line. Default is 20 characters (if provided) - `break.label.summary`: boolean to indicate if new line should start in label before (n, event) summary. Default is FALSE ## Returns ggplot object of caterpillar plot ## Examples ```r data("ae"); ae$G3Plus <- 0; ae$G3Plus[ae$AE_SEV_GD %in% c("3", "4", "5")] <- 1; ae$Drug_1_Attribution <- 0; ae$Drug_1_Attribution[ae$CTC_AE_ATTR_SCALE %in% c("Definite", "Probable", "Possible")] <- 1; ae$Drug_2_Attribution <- 0; ae$Drug_2_Attribution[ae$CTC_AE_ATTR_SCALE_1 %in% c("Definite", "Probable", "Possible")] <- 1; prior2RE <- list(R = list(V = diag(1), fix = 1), G=list(G1=list(V=1, nu=0.02), G2=list(V=1, nu=0.02))); model1 <- MCMCglmm::MCMCglmm(G3Plus ~ Drug_1_Attribution + Drug_2_Attribution, random=~Subject + ae_category, family="categorical", data=ae, saveX=TRUE, verbose=FALSE, burnin=2000, nitt=10000, thin=10, pr=TRUE, prior=prior2RE); p <- caterpillar_plot(subjID = "Subject", mcmcglmm_object = model1, prob = 0.99, orig_dataset = ae, binaryOutcomeVar = "G3Plus") p <- caterpillar_plot(subjID = "ae_category", mcmcglmm_object = model1, prob = 0.95, orig_dataset = ae, remove.text.subjID = FALSE, ncol = 4, binaryOutcomeVar = "G3Plus", subtitle = "System organ class (n, event)", title = "Odds Ratio for G3+ Severity with 95% Highest Posterior Density Interval", fonts = c("Arial", "Arial", "Arial", "Arial"), break.label.summary = TRUE) ```

caterpillar_plot function