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1 Package coefplot February 15, 2013 Type Package Title Plots Coefficients from Fitted Models Version Date Author Jared P. Lander Maintainer Plots the coefficients from a model object License BSD LazyLoad yes Depends ggplot2 Imports plyr, stringr, reshape2, useful Collate coefplot.r modelinfo.r utilities.r coefplot-package.r multiplot.r ByteCompile TRUE Repository CRAN Date/Publication :20:14 NeedsCompilation no R topics documented: buildmodelci buildplotting.lm coefplot coefplot.lm coefplot.rxlinmod coefplot.rxlogit getmodelinfo

2 2 buildmodelci getmodelinfo.lm getmodelinfo.rxlinmod getmodelinfo.rxlogit meltmodelci multiplot Index 18 buildmodelci Build data.frame for plotting Builds a data.frame that is appropriate for plotting coefficients buildmodelci(model, outerci = 2, innerci = 1, intercept = TRUE, numeric = FALSE, sort = c("natural", "normal", "magnitude", "size", "alphabetical"), decreasing = TRUE, name = NULL,...) model innerci outerci sort decreasing numeric intercept The fitted model to build information on How wide the inner confidence interval should be, normally 1 standard deviation. If 0, then there will be no inner confidence interval. How wide the outer confidence interval should be, normally 2 standard deviations. If 0, then there will be no outer confidence interval. Determines the sort order of the coefficients. Possible values are c("natural", "normal", "magnitude", "size", "alphabetical") logical; Whether the coefficients should be ascending or descending logical; If true and factors has exactly one value, then it is displayed in a horizontal graph with constinuous confidence bounds. logical; Whether the Intercept coefficient should be plotted... See for information on factors, only and shorten name A name for the model, if NULL the call will be used This is the workhorse for coefplot, it get s the data all prepared factors Vector of factor variables that will be the only ones shown only logical; If factors has a value this determines how interactions are treated. True means just that variable will be shown and not its interactions. False means interactions will be included.

3 buildplotting.lm 3 shorten logical or character; If FALSE then coefficients for factor levels will include their variable name. If TRUE coefficients for factor levels will be stripped of their variable names. If a character vector of variables only coefficients for factor levels associated with those variables will the variable names stripped. Otherwise a data.frame listing coeffcients and confidence bands is returned. Jared P. Lander coefplot multiplot model1 <- lm(price ~ carat + cut, data=diamonds) model2 <- lm(price ~ carat, data=diamonds) model3 <- lm(price ~ carat + cut + color, data=diamonds) coefplot:::buildmodelci(model1) #coefplot(model1) #coefplot(model2) #coefplot(model3) #coefplot(model3, factors="cut") #coefplot(model3, factors="cut", numeric=t) #coefplot(model3, shorten="cut") buildplotting.lm Coefplot plotting Build ggplot object for coefplot buildplotting.lm(modelci, modelmeltinner = NULL, modelmeltouter = NULL, title = "Coefficient Plot", xlab = "", ylab = "Coefficient", lwdinner = 1, lwdouter = 0, color = "blue", cex = 0.8, textangle = 0, numberangle = 0, outerci = 2, innerci = 1, multi = FALSE, zerocolor = "grey", zerolwd = 1, zerotype = 2, numeric = FALSE, fillcolor = "grey", alpha = 1/2, horizontal = FALSE, facet = FALSE, scales = "free")

4 4 buildplotting.lm modelci An object created by buildmodelci modelmeltinner The inner SE part of the object built by meltmodelci modelmeltouter The outer SE part of the object built by meltmodelci title xlab ylab innerci outerci multi lwdinner lwdouter color cex textangle numberangle The name of the plot, if NULL then no name is given The x label The y label How wide the inner confidence interval should be, normally 1 standard deviation. If 0, then there will be no inner confidence interval. How wide the outer confidence interval should be, normally 2 standard deviations. If 0, then there will be no outer confidence interval. logical; If this is for multiplot then dodge the geoms The thickness of the inner confidence interval The thickness of the outer confidence interval The color of the points and lines The text size multiplier, currently not used The angle for the coefficient labels, 0 is horizontal The angle for the value labels, 0 is horizontal zerocolor The color of the line indicating 0 zerolwd zerotype facet scales numeric fillcolor alpha horizontal The thickness of the 0 line The type of 0 line, 0 will mean no line logical; If the coefficients should be faceted by the variables, numeric coefficients (including the intercept) will be one facet The way the axes should be treated in a faceted plot. Can be c("fixed", "free", "free_x", "free_y") logical; If true and factors has exactly one value, then it is displayed in a horizontal graph with constinuous confidence bounds. The color of the confidence bounds for a numeric factor The transparency level of the numeric factor s confidence bound logical; If the plot should be displayed horizontally This function builds up the ggplot layer by layer for coefplot.lm a ggplot graph object Jared P. Lander

5 coefplot 5 coefplot.lm coefplot multiplot model1 <- lm(price ~ carat + cut, data=diamonds) theci <- coefplot:::buildmodelci(model1) thecimelt <- coefplot:::meltmodelci(theci) coefplot:::buildplotting.lm(theci, thecimelt$modelmeltinner, thecimelt$modelmeltinner) coefplot Dotplot for model coefficients A graphical display of the coefficients and standard errors from a fitted model Provides an S3 generic method for plotting coefficients from a model so it can be extended to other model types. coefplot(model,...) model The fitted model with coefficients to be plotted... See coefplot.lm for argument details coefplot is the S3 generic method for plotting the coefficients from a fitted model. This can be extended with new methods for other types of models not currently available. A future iteration of coefplot.glm will also allow for plotting the coefficients on the transformed scale. See coefplot.lm for specific documentation and the return value. Currently, methods are available for lm, glm and rxlinmod objects. A ggplot2 object or data.frame. See details in coefplot.lm for more information Jared P. Lander

6 6 coefplot.lm coefplot.lm head(diamonds) model1 <- lm(price ~ carat + cut*color, data=diamonds) model2 <- lm(price ~ carat*color, data=diamonds) coefplot(model1) coefplot(model1, shorten=false) coefplot(model1, shorten=c("cut")) coefplot(model1, shorten=c("cut"), intercept=false) coefplot(model1, factors="cut") coefplot(model1, factors="cut", only=true) coefplot(model1, facet=true) coefplot(model2) coefplot.lm Dotplot for lm coefficients A graphical display of the coefficients and standard errors from a fitted lm model ## S3 method for class lm coefplot(model, title = "Coefficient Plot", xlab = "", ylab = "Coefficient", innerci = 1, outerci = 2, lwdinner = 1, lwdouter = 0, color = "blue", cex = 0.8, textangle = 0, numberangle = 0, zerocolor = "grey", zerolwd = 1, zerotype = 2, facet = FALSE, scales = "free", sort = c("natural", "normal", "magnitude", "size", "alphabetical"), decreasing = FALSE, numeric = FALSE, fillcolor = "grey", alpha = 1/2, horizontal = FALSE, factors = NULL, only = NULL, shorten = TRUE, intercept = TRUE, plot = TRUE,...) model title xlab ylab The model we are graphing The name of the plot, if NULL then no name is given The x label The y label

7 coefplot.lm 7 innerci outerci lwdinner lwdouter color cex textangle numberangle How wide the inner confidence interval should be, normally 1 standard deviation. If 0, then there will be no inner confidence interval. How wide the outer confidence interval should be, normally 2 standard deviations. If 0, then there will be no outer confidence interval. The thickness of the inner confidence interval The thickness of the outer confidence interval The color of the points and lines The text size multiplier, currently not used The angle for the coefficient labels, 0 is horizontal The angle for the value labels, 0 is horizontal zerocolor The color of the line indicating 0 zerolwd zerotype facet scales sort decreasing numeric fillcolor alpha horizontal intercept plot factors only shorten The thickness of the 0 line The type of 0 line, 0 will mean no line logical; If the coefficients should be faceted by the variables, numeric coefficients (including the intercept) will be one facet The way the axes should be treated in a faceted plot. Can be c("fixed", "free", "free_x", "free_y") Determines the sort order of the coefficients. Possible values are c("natural", "normal", "magnitude", "size", "alphabetical") logical; Whether the coefficients should be ascending or descending logical; If true and factors has exactly one value, then it is displayed in a horizontal graph with constinuous confidence bounds. The color of the confidence bounds for a numeric factor The transparency level of the numeric factor s confidence bound logical; If the plot should be displayed horizontally logical; Whether the Intercept coefficient should be plotted logical; If the plot should be drawn, if false then a data.frame of the values will be returned Vector of factor variables that will be the only ones shown logical; If factors has a value this determines how interactions are treated. True means just that variable will be shown and not its interactions. False means interactions will be included. logical or character; If FALSE then coefficients for factor levels will include their variable name. If TRUE coefficients for factor levels will be stripped of their variable names. If a character vector of variables only coefficients for factor levels associated with those variables will the variable names stripped.... passed on to other functions coefplot is the S3 generic method for plotting the coefficients from a fitted model. This method also plots coefficients from glm (using coefplot.lm) and rxlinmod models (through a redirection from coefplot.rxlinmod)

8 8 coefplot.rxlinmod If plot is TRUE then a ggplot object is returned. Otherwise a data.frame listing coeffcients and confidence bands is returned. Jared P. Lander lm glm ggplot coefplot plotcoef head(diamonds) model1 <- lm(price ~ carat + cut*color, data=diamonds) model2 <- lm(price ~ carat*color, data=diamonds) coefplot(model1) coefplot(model1, shorten=false) coefplot(model1, shorten=c("cut")) coefplot(model1, shorten=c("cut"), intercept=false) coefplot(model1, factors="cut") coefplot(model1, factors="cut", only=true) coefplot(model1, facet=true) coefplot(model2) coefplot.rxlinmod Dotplot for rxlinmod coefficients A graphical display of the coefficients and standard errors from a fitted rxlinmod model ## S3 method for class rxlinmod coefplot(...)... All arguments are passed on to coefplot.lm. Please see that function for argument information. coefplot is the S3 generic method for plotting the coefficients from a fitted model. For more information on this function and it s arguments see coefplot.lm

9 coefplot.rxlogit 9 A ggplot object. See coefplot.lm for more information. Jared P. Lander # See coefplot.lm for examples coefplot.rxlogit Dotplot for rxlogit coefficients A graphical display of the coefficients and standard errors from a fitted rxlogit model ## S3 method for class rxlogit coefplot(...)... All arguments are passed on to coefplot.lm. Please see that function for argument information. coefplot is the S3 generic method for plotting the coefficients from a fitted model. For more information on this function and it s arguments see coefplot.lm A ggplot object. See coefplot.lm for more information. Jared P. Lander # See coefplot.lm for examples

10 10 getmodelinfo getmodelinfo Model Information Extracts and builds extensive information from models getmodelinfo(model,...) model The fitted model with coefficients to be plotted... Further arguments such as shorten, only and factors Helper function for coefplot Information on the model Jared P. Lander coefplot.lm model1 <- lm(price ~ carat + cut*color, data=diamonds) coefplot(model1)

11 getmodelinfo.lm 11 getmodelinfo.lm Model Information Extracts and builds extensive information from lm and glm models getmodelinfo.lm(model, shorten = TRUE, factors = NULL, only = NULL,...) model factors only shorten The fitted model with coefficients to be plotted Vector of factor variables that will be the only ones shown logical; If factors has a value this determines how interactions are treated. True means just that variable will be shown and not its interactions. False means interactions will be included. logical or character; If FALSE then coefficients for factor levels will include their variable name. If TRUE coefficients for factor levels will be stripped of their variable names. If a character vector of variables only coefficients for factor levels associated with those variables will the variable names stripped.... Further arguments Helper function for coefplot Information on the model Jared P. Lander coefplot.lm model1 <- lm(price ~ carat + cut*color, data=diamonds) coefplot(model1)

12 12 getmodelinfo.rxlinmod getmodelinfo.rxlinmod Model Information for rxlinmod Extracts and builds extensive information from rxlinmod models getmodelinfo.rxlinmod(model, shorten = TRUE, factors = NULL, only = NULL,...) model factors only shorten The fitted model with coefficients to be plotted Vector of factor variables that will be the only ones shown logical; If factors has a value this determines how interactions are treated. True means just that variable will be shown and not its interactions. False means interactions will be included. logical or character; If FALSE then coefficients for factor levels will include their variable name. If TRUE coefficients for factor levels will be stripped of their variable names. If a character vector of variables only coefficients for factor levels associated with those variables will the variable names stripped.... Further arguments Helper function for coefplot Information on the model Jared P. Lander coefplot.lm coefplot getmodelinfo.rxlinmod model1 <- lm(price ~ carat + cut*color, data=diamonds) coefplot(model1)

13 getmodelinfo.rxlogit 13 getmodelinfo.rxlogit Model Information for rxlogit Extracts and builds extensive information from rxlogit models getmodelinfo.rxlogit(...)... Further arguments. See getmodelinfo.rxlinmod for more information on this function s arguments. Helper function for coefplot See getmodelinfo.rxlinmod for more information on this function s arguments as it is simply a wrapper function. Information on the model Jared P. Lander coefplot.lm coefplot model1 <- lm(price ~ carat + cut*color, data=diamonds) coefplot(model1)

14 14 meltmodelci meltmodelci Melt the modelci Melt a modelci into a form suitable for plotting meltmodelci(modelci, keepcols = c("lowouter", "HighOuter", "LowInner", "HighInner", "Coef", "Checkers", "CoefShort"), id.vars = c("coefshort", "Checkers"), variable.name = "Type", value.name = "value", outercols = c("lowouter", "HighOuter"), innercols = c("lowinner", "HighInner")) modelci keepcols id.vars variable.name value.name innercols outercols A data.frame as built by buildmodelci The columns in modelci that should be kept as there can be extras The columns to use as ID variables in melt Used in melt for naming the column that stores the melted variables Used in melt for naming the column that stores the melted values The columns to be included in the data.frame of inner standard errors The columns to be included in the data.frame of outer standard errors buildmodelci builds a data.frame for plotting. This function melts it into plottable form and seperates the coefficient data from the SE data into seprate data.frames A list consisting of modelmelt Melted modelci with all values modelmeltouter modelmelt with only values associated with the outer standard errors modelmeltinner modelmelt with only values associated with the inner standard errors Jared P. Lander coefplot buildmodelci

15 multiplot 15 model1 <- lm(price ~ carat + cut, data=diamonds) modeled <- coefplot:::buildmodelci(model1) coefplot:::meltmodelci(modeled) multiplot Plot multiple coefplots Plot the coeffcients from multiple models multiplot(..., title = "Coefficient Plot", xlab = "", ylab = "Coefficient", innerci = 1, outerci = 2, lwdinner = 1, lwdouter = 0, color = "blue", cex = 0.8, textangle = 0, numberangle = 90, zerocolor = "grey", zerolwd = 1, zerotype = 2, single = TRUE, scales = "fixed", ncol = length(unique(modelci$model)), sort = c("natural", "normal", "magnitude", "size", "alphabetical"), decreasing = FALSE, names = NULL, numeric = FALSE, fillcolor = "grey", alpha = 1/2, horizontal = FALSE, factors = NULL, only = NULL, shorten = TRUE, intercept = TRUE, plot = TRUE, drop = FALSE)... Models to be plotted title xlab ylab innerci outerci lwdinner lwdouter color cex textangle numberangle The name of the plot, if NULL then no name is given The x label The y label How wide the inner confidence interval should be, normally 1 standard deviation. If 0, then there will be no inner confidence interval. How wide the outer confidence interval should be, normally 2 standard deviations. If 0, then there will be no outer confidence interval. The thickness of the inner confidence interval The thickness of the outer confidence interval The color of the points and lines The text size multiplier, currently not used The angle for the coefficient labels, 0 is horizontal The angle for the value labels, 0 is horizontal

16 16 multiplot zerocolor The color of the line indicating 0 zerolwd zerotype single scales ncol sort decreasing names numeric fillcolor alpha horizontal intercept plot factors only shorten drop The thickness of the 0 line The type of 0 line, 0 will mean no line logical; If TRUE there will be one plot with the points and bars stacked, otherwise the models will be displayed in seperate facets The way the axes should be treated in a faceted plot. Can be c("fixed", "free", "free_x", "free_y") The number of columns that the models should be plotted in Determines the sort order of the coefficients. Possible values are c("natural", "normal", "magnitude", "size", "alphabetical") logical; Whether the coefficients should be ascending or descending Names for models, if NULL then they will be numerically labelled logical; If true and factors has exactly one value, then it is displayed in a horizontal graph with constinuous confidence bounds. The color of the confidence bounds for a numeric factor The transparency level of the numeric factor s confidence bound logical; If the plot should be displayed horizontally logical; Whether the Intercept coefficient should be plotted logical; If the plot should be drawn, if false then a data.frame of the values will be returned Vector of factor variables that will be the only ones shown logical; If factors has a value this determines how interactions are treated. True means just that variable will be shown and not its interactions. False means interactions will be included. logical or character; If FALSE then coefficients for factor levels will include their variable name. If TRUE coefficients for factor levels will be stripped of their variable names. If a character vector of variables only coefficients for factor levels associated with those variables will the variable names stripped. logical; if TRUE then models without valid coeffiecients to show will not be plotted Plots a graph similar to coefplot but for multiple plots at once. For now, if names is provided the plots will appear in alphabetical order of the names. This wil be adjusted in future iterations. A ggplot object link{coefplot}

17 multiplot 17 model1 <- lm(price ~ carat + cut, data=diamonds) model2 <- lm(price ~ carat + cut + color, data=diamonds) model3 <- lm(price ~ carat + color, data=diamonds) multiplot(model1, model2, model3) multiplot(model1, model2, model3, single=false) multiplot(model1, model2, model3, factors="color") multiplot(model1, model2, model3, factors="color", drop=true) multiplot(model1, model2, model3, plot=false)

18 Index Topic coefficients coefplot, 5 Topic coefficient coefplot, 5 Topic coefplot coefplot, 5 Topic dotplot coefplot, 5 Topic glm coefplot, 5 Topic linear coefplot, 5 Topic lm coefplot, 5 Topic model coefplot, 5 Topic rxlinmod coefplot, 5 multiplot, 3 5, 15 plotcoef, 8 plotcoef (coefplot), 5 buildmodelci, 2, 4, 14 buildplotting.lm, 3 coefplot, 3, 5, 5, 7 14, 16 coefplot-package (coefplot), 5 coefplot.lm, 4 6, 6, 8 13 coefplot.rxlinmod, 8 coefplot.rxlogit, 9 data.frame, 3, 8, 14 getmodelinfo, 10 getmodelinfo.lm, 11 getmodelinfo.rxlinmod, 12, 12, 13 getmodelinfo.rxlogit, 13 ggplot, 8 glm, 8 lm, 8 melt, 14 meltmodelci, 4, 14 18

Package coefplot. R topics documented: January 4, 2018

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