sjPlot - data visualization for statistics in social science


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Documentation for package ‘sjPlot’ version 1.3

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sjPlot-package sjPlot - data visualization for statistics in social science
efc Sample dataset from the EUROFAMCARE project
sjc.cluster Compute hierarchical or kmeans cluster analysis
sjc.dend Compute hierarchical cluster analysis and visualize group classification
sjc.elbow Compute elbow values of a k-means cluster analysis
sjc.grpdisc Compute a linear discriminant analysis on classified cluster groups
sjc.kgap Compute gap statistics for k-means-cluster
sjc.qclus Compute quick cluster analysis
sji.convertToLabel Replaces variable values with their associated value labels
sji.convertToValue Converts factors to numeric variables
sji.getValueLabels Retrieve value labels of an SPSS-imported data frame
sji.getVariableLabels Retrieve variable labels of an SPSS-imported data frame
sji.setValueLabels Attach value labels to a variable or vector
sji.setVariableLabels Set variable label(s) to a single variable or data frame
sji.SPSS Import SPSS dataset as data frame into R
sji.viewSPSS View SPSS data set structure
sjp.aov1 Plot One-Way-Anova tables
sjp.chi2 Plot Pearson's Chi2-Test of multiple contingency tables
sjp.corr Plot correlation matrix
sjp.frq Plot frequencies of (count) variables
sjp.glm Plot odds ratios (forest plots)
sjp.glm.ma Plot model assumptions of glm's
sjp.glmm Plot odds ratios (forest plots) of multiple fitted glm's
sjp.grpfrq Plot grouped or stacked frequencies
sjp.likert Plot likert scales as centered stacked bars
sjp.lm Plot beta coefficients of lm
sjp.lm.int Plot interaction terms of linear models
sjp.lm.ma Plot model assumptions of lm's
sjp.lm1 Plot regression line of fitted lm
sjp.lmm Plot beta coefficients of multiple fitted lm's
sjp.pca Plot PCA results
sjp.reglin Plot regression lines for each predictor
sjp.scatter Plot (grouped) scatter plots
sjp.stackfrq Plot stacked proportional bars
sjp.vif Plot Variance Inflation Factors of linear models
sjp.xtab Plot contingency tables
sjPlot sjPlot - data visualization for statistics in social science
sjt.corr Show correlations as HTML table
sjt.df Show (description of) data frame as HTML table
sjt.frq Show frequencies as HTML table
sjt.glm Show (and compare) generalized linear models as HTML table
sjt.itemanalysis Show item analysis of an item scale as HTML table
sjt.lm Show linear regression as HTML table
sjt.pca Show principal component analysis as HTML table
sjt.stackfrq Show stacked frequencies as HTML table
sjt.xtab Show contingency tables as HTML table
sju.adjustPlotRange.y Adjust y range of ggplot-objects
sju.aov1.levene Plot Levene-Test for One-Way-Anova
sju.betaCoef Retrieve std. beta coefficients of lm
sju.chi2.gof Performs a Chi-square goodness-of-fit-test
sju.cramer Cramer's V for a contingency table
sju.cronbach Calculates Cronbach's Alpha for a matrix
sju.dicho Dichotomize variables
sju.groupVar Recode count variables into grouped factors
sju.groupVarLabels Create labels for recoded groups
sju.mwu Performs a Mann-Whitney-U-Test
sju.phi Phi value for a contingency table
sju.recode Recode variable values.
sju.recodeTo Recode variable categories into new values.
sju.reliability Performs a reliability test on an item scale.
sju.setNA Set NA for specific variable values
sju.table.values Compute table's values
sju.weight Weight a variable
sju.weight2 Weight a variable
sju.wordwrap Insert line breaks in long labels