CluMP_view: Cluster profiles' (CluMP results) visualisation

Description

This graphical function enables to visualise cluster profiles (mean representatives of each cluster). Available are three types of plots: non-parametric (LOESS method for small/medium or GAM method for complex data of large size. Both methods are applied from ggplot2 representatives (mean within-cluster trajectories) with/without all individual (original) trajectories, and nonparametric mean trajectories with error bars.

Usage

CluMP_view(CluMPoutput, type = "all", nb_intervals = NULL,
  return_table = FALSE, title = NULL, x_title = NULL,
  y_title = NULL, plot_NA = FALSE)

Arguments

CluMPoutput

An object (output) from the CluMP function.

type

String. Indicates which type of graph is required. Possible values for this argument are: "all" (plots all data with non-parametric mean trajectories), "cont" (only non-parametric mean trajectories) or "breaks" (mean trajectories with error bars).

nb_intervals

An integer, positive number (scalar) specifying the number of regular timepoints into which should be follow-up period split. This argument works only with graph type = "breaks". In case of other graph types the argument is ignored. The number of error bars is equal to the number of timepoints specified by this argument.

return_table

Logical scalar indicating if the summary table of plotted values in the graph of type = "breaks" should be returned. Default is FALSE.

title

String. Optional title for a plot. If undefined, no title will used.

x_title

String. An optional title for x axis. If undefined, the variable name after ~ in formula will used.

y_title

String. An optional title for y axis. If undefined, the variable name before ~ in formula will used.

plot_NA

Plot NA cluster if exists. Default is FALSE. NA cluster gathers improper individuals (< 3 observations) for longitudinal clustering.

Value

Returns graph for type "all" and "cont" or (list with) graph and table of mean trajectories (if specified) for type = "breaks".

Examples

Run this code

# NOT RUN {
dataMale <- GeneratePanel(n = 50, Param = ParamLinear, NbVisit = 10)
dataMale$Gender <- "M"
dataFemale <- GeneratePanel(n = 50, Param = ParamLinear, NbVisit = 10)
dataFemale$ID <- dataFemale$ID + 50
dataFemale$Gender <- "F"
data <- rbind(dataMale, dataFemale)

CluMPoutput <- CluMP(formula = Y ~ Time, group = "ID", data = data, cl_numb = 3)
title <- "Plotting clusters' representatives with error bars"
CluMP_view(CluMPoutput, type = "all" , return_table = TRUE, title = title)
CluMP_view(CluMPoutput, type = "cont")
CluMP_view(CluMPoutput, type = "breaks", nb_intervals = 5, return_table=TRUE)

# }

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