All functions
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BGMtest()
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Tests the five Berry, Golder and Milton (2012) Interactive Hypothesis |
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DAMisc-package
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Dave Armstrong's Miscellaneous Functions |
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DAintfun()
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Surface Plots for Two-Way Interactions |
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DAintfun2()
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Conditional Effects Plots for Interactions in Linear Models |
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DAintfun3()
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Conditional Effects Plots for Interactions in Linear Models |
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InteractionEx
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Example Data for DAintfun |
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NKnots()
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AIC and BIC selection of number of spline knots |
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NKnotsTest()
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Test of functional form assumption using B-splines |
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aclp
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Example data for btscs function |
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alsosDV()
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Alternating Least Squares Optimal Scaling |
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aveEffPlot()
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Average Effect Plot for Generalized Linear Models |
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balsos()
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Bayesian Alternating Least Squares Optimal Scaling |
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binfit()
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Scalar Measures of Fit for Binary Variable Models |
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btscs()
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Generate Spells for Binary Variables |
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cat2Table()
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Fitted Values and CIs for 2-Categorical Interactions |
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changeSig()
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Regions of Statistical Significance in Interactions |
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combTest()
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Test for Combining Categories in Multinomial Logistic Regression Models. |
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crSpanTest()
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Test of Span Parameter in linearity for Component + Residual Plots |
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crTest()
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Test of linearity for Component + Residual Plots |
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cv.lo2()
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Cross-validating Loess curve |
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effect_logistf()
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Plot Effects from Firth Logit |
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france
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Example data for factorplot function |
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glmChange()
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Maximal First Differences for Generalized Linear Models |
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glmChange2()
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Maximal First Differences for Generalized Linear Models |
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inspect()
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Inspect a Variable in a Data Frame |
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intEff()
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Functions for Estimating Interaction Effects in Logit and Probit Models |
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intQualQuant()
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Predictions for Factor-Numeric Interactions in Linear Models |
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loessDeriv()
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Estimate Derivatives of LOESS Curve. |
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logit_cc()
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Functions for Estimating Interaction Effects in Logit and Probit Models |
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makeHypSurv()
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Make Hypothetical Predictions for Survey Data |
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mnlAveEffPlot()
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Average Effects Plot for Multinomial Logistic Regression |
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mnlChange()
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Maximal First Differences for Multinomial Logistic Regression Models |
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mnlChange2()
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Average Effects for Multinomial Logistic Regression Models |
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mnlSig()
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Print Statistically Significant MNL Coefficients |
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mnlfit()
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Fit Statistics and Specification Test for Multinomial Logistic Regression |
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oc2plot()
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Plot First Differences from Ordinal DV Model |
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ordAveEffPlot()
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Plot Average Effects of Variables in Proportional Odds Logistic Regression |
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ordChange()
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Maximal First Differences for Proportional Odds Logistic Regression Models |
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ordChange2()
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Average Effects for Proportional Odds Logistic Regression Models |
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ordfit()
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Fit Statistics for Proportional Odds Logistic Regression Models |
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outEff()
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Plot Effects of Removing Outliers |
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outXT()
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Create LaTeX or CSV versions of an Object Produced by CrossTable |
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panel.2cat()
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Lattice panel function for confidence intervals with capped bars |
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panel.ci()
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Lattice panel function for confidence intervals |
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panel.doublerug()
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Lattice panel function for two rug plots |
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panel.transci()
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Lattice panel function for translucent confidence intervals |
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plot(<balsos>)
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Plot Results from BALSOS |
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plot(<loess>)
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Plot LOESS curve. |
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secondDiff()
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Calculate Cross-Derivative and its Variability |
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poisGOF()
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Deviance and Chi-squared Goodness-of-Fit Test for Poisson Models |
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poisfit()
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Scalar Measures of Fit for Poisson GLMs Models |
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powerTrans()
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Power Transformation Function |
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pre()
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Proportional and Expected Proportional Reductions in Error |
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prepanel.ci()
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Lattice prepanel function for confidence intervals |
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print(<diffci>)
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Print Confidence Intervals for Predicted Probabilities and Their Differences |
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print(<glmc2>)
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Print method for glmChange objects |
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print(<iqq>)
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Print method for intQualQuant objects. |
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print(<ordChange>)
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Print method for ordChange objects |
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print(<pre>)
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Print method for objects of class pre |
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probci()
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Confidence Intervals for Predicted Probabilities and Their Differences |
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probgroup()
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Plog Probabilities by Group |
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scaleDataFrame()
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Standardize quantitative variables in a data frame |
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searchVarLabels()
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Search Variable Labels Attribute |
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simPredpolr()
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Calculate Predictions for Proportional Odds Logistic Regression |
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summary(<balsos>)
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Summry method for Bayesian ALSOS |
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summary(<secdiff>)
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Summary for Second Difference Objects |
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test.balsos()
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Testing Measurement Level Assumptions. |
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testGAMint()
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Simulated F-test for Linear Interactions |
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testLoess()
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Significance Test for Loess vs. LM |
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testNL()
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Test Transformations and Polynomials in Non-linear Models |
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tscslag()
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Lag a time-series cross-sectional variables |
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yj_trans()
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Optimizing Yeo-Johnson Transformation |
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ziChange()
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Maximal First Differences for Zero-Inflated Models |