Index of vignette topics

Jump to: A B C D E F G H I J K L M N O P Q R S T U V W X Z

A

• add_grouping()
• addl.vars
• adjust
  • in comparisons: pairwise
  • in confidence-intervals: adjust
  • vs. cross.adjust
• Adjusted means
• Adjusted R-squared
• afex_aov objects
• Alias matrix
• Analysis of subsets of data
• Analysis of variance
  • versus post hoc comparisons
  • Type III
• aovList objects
• appx-satterthwaite method
• Arguments
  • ...
  • Passed to ref_grid()
• as.mcmc()
  • in models: S
  • in sophisticated: bayesxtra
• ASA Statement on P values
• Asymptotic tests
• ATOM
• averaging models

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B

• Back-transforming
• Balanced allocation
• Bayes factor
• Bayesian models
  • in models: S
  • in sophisticated: mcmc
• bayesplot package
• bayestestR package
• Beta regression
• betareg models
• Bias adjustment
  • For link functions vs. response transformations
  • in Bayesian models
  • In GLMMs and GEE models
  • When back-transforming
  • When not to use
  • with random slopes
• Bonferroni adjustment
• boot-satterthwaite method
• Brackets ([ ] and [[ ]] operators)
• brmsfit objects
• by groups
  • Adjusting across groups
  • Identical comparisons

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C

• Causal inference
• cld()
• clm models
• coda package
• coef()
• Cohen’s d
• Compact letter displays
• Comparison arrows
  • Derivation
• Comparisons
  • Back-transforming
  • Displaying as groups
  • Displaying P values
  • Graphical
    • How arrows are determined
  • with logs
  • Obtaining differences rather than ratios
  • with overlapping CIs
• Comparisons result in (nothing)
• Confidence intervals
  • Overlapping
• confint()
• Confounded effects
• Confounding
• consec contrasts
• Constrained marginal means
• Consultants
• Containment d.f.
• contrast()
  • adjust
  • Changing defaults
  • combine
  • interaction
  • Linear functions
  • simple
    • in confidence-intervals: simple
    • in interactions: simple
• Contrasts
  • of other contrasts
  • Custom
  • Formula
  • Multivariate
  • Pairwise
  • Polynomial
  • Tests of
    • with transformations
• Controlled experiments
• Count regression
• Counterfactuals
• cov.reduce
• Covariates
  • Adjusted
  • cov.keep
  • cov.reduce
  • Derived
  • emmeans() doesn’t work
  • Interacting with factors
  • Mediating
• cross-group comparisons
• cross.adjust

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D

• Degrees of freedom
  • Infinite
• Digits
  • Displaying more digits
• Digits, optimizing
• Dunnett method

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E

• eff contrasts
• eff_size()
• Effect size
• emm_basis()
  • Arguments and returned value
  • Communicating with recover_data()
  • Dispatching
  • Hook functions
  • for lqs objects
  • Re-gridded
  • for rsm objects
• emm_list object
• emm_options()
• .emmc functions
• emmeans package
  • Exporting extensions to
  • Quick-start guide
• emmeans()
  • And the underlying model
  • Arguments passed to ref_grid()
  • Changing defaults
  • Fastest way to get wrong answers
  • Surprising results from
  • weights
    • in basics: weights
    • in messy-data: weights
  • With transformations
• emmGrid objects
  • Accessing data
  • Combining and subsetting
  • Modifying
  • Setting defaults for
• emmip()
  • in basics: emmip
  • in basics: plots
  • in interactions: factors
  • nested factors
• EMMs
  • Projecting to a submodel
  • What are they?
• emtrends()
  • in interactions: covariates
  • in interactions: oranges
• estHook
• Estimability
• Estimability issues
• Estimable functions
• Estimated marginal means
  • Definition of
  • Demonstrated
  • Manually computed
  • Reference grid
  • vs. ordinary marginal means
• Examples
  • auto.noise
  • Bayesian model
  • cbpp
    • in sophisticated: mcmc
    • in transformations: cbpp
  • ChickWeight
  • cows
  • feedlot
  • fiber
    • in interactions: covariates
    • in transformations: stdize
  • framing
  • Gamma regression
  • InsectSprays
  • Insurance
  • Insurance claims (SAS)
  • Logistic regression
  • lqs objects
  • MOats
  • mtcars
    • in basics: depcovs
    • in messy-data: nuis.example
  • Multivariate
  • Nested fixed effects
  • neuralgia
    • counterfactuals
    • in transformations: links
    • in transformations: trangraph
  • nutrition
    • submodel
    • weights
  • Oats
  • oranges
    • in comparisons: formulas
    • in interactions: oranges
  • Ordinal model
  • pigs
    • in basics: pigs
    • in confidence-intervals: summary
    • in transformations: altscale
    • in transformations: overview
    • in transformations: pigs-biasadj
  • rlm objects
  • Robust regression
  • Split-plot experiment
  • Unbalanced data
  • warpbreaks
    • in confidence-intervals: cross-adjust
    • in transformations: tranlink
    • in utilities: relevel
  • Welch’s t comparisons
  • wine
• Expected marginal means
  • Foundations of
  • Reliance on a model
• Experimental versus observational data
• Exporting output
• Extending emmeans
  • Exports useful to developers
  • Restrictions

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F

• F test
  • vs. pairwise comparisons
  • Role in post hoc tests
• Factors
  • Mediating
• Formatting results
• Foundations of EMMs
• Frequently asked questions

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G

• G-Computation
• gam models
• gamlss models
• GEE models
• Generalized additive models
• Generalized linear models
• Geometric means
• Get the model right first
• get_emm_option()
• ggplot2 package
  • in basics: ggplot
  • in messy-data: cows
• GIGO (garbage in, garbage out)
• glmxxx models
• gls models
• Graphical displays
• Grouping factors
• Grouping into separate sets

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H

• Hook functions
• Hotelling’s T²
• hpd.summary()
• hurdle models

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I

• Indicator variables
• Infinite degrees of freedom
• Interaction-style plots
• Interactions
  • Analysis
  • Contrasts
  • Covariate with factors
  • Implied
  • Plotting
  • Possible inappropriateness of marginal means
• inverse()

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J

• joint
• joint_tests()
  • in confidence-intervals: joint_tests
  • Confounded effects
  • in interactions: contrasts
  • with submodel = "type2"

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K

• kable
• Kenward-Roger d.f.

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L

• Labels
  • Changing
• Large models
• Latin squares
• Least-squares means
• Levels
  • Changing
• Linear functions
• Link functions
• lme models
• lmerMod models
  • in models: L
  • in sophisticated: lmer
  • System options for
• Logistic-like regression
  • Non-logit links
• Logistic regression
  • Odds ratios
  • Risk ratios
  • Surprising results
• LSD
  • protected

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M

• make.tran()
• mcmc objects
• Means
  • Generalized
  • Weighted
• Mediating covariates
• Memory usage
  • Limiting
• mira models
• misc attribute and argument
• misc$regrid.flag
• Missing cells
• mlm models
• mmer models
• mode argument
  • implied re-gridding
• Model
  • Get it right first
  • Importance of
    • in basics: models
    • in FAQs: fastest
  • Importance of getting it right
• Model averaging
• Modeling
  • pigs example
  • Response transformation
• Modelling
• Models
  • Constrained
  • Large
  • Quick reference
  • Unsupported
• Multi-factor studies
• Multinomial models
• Multiple imputation
• Multiplicity adjustments
• Multivariate contrasts
• Multivariate models
  • in basics: multiv
  • in interactions: oranges
  • in models: M
  • with submodel
• Multivariate t ("mvt") adjustment
• mvcontrast()
• mvtnorm package

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N

• NAs in the output
• Nesting
  • Auto-detection
• Nesting factors
  • Creating
• Non-estimability
• non.nuisance
• NonEst values
• (nothing) in output
• nuisance
• Nuisance factors

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O

• Observational data
  • in basics: weights
  • in messy-data: issues
• Observational versus experimental data
• Odds ratios
  • but I wanted differences
• Offsets
  • Models with offsets
  • offset() term vs. offset argument in model
• Only one mean
• opt.digits option
• Options
  • Startup
• Ordinal models
  • Latent scale
  • Linear-predictor scale
  • in models: O
  • prob and mean.class
  • in sophisticated: ordinal

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P

• P values
  • Adjusted
  • Adjustment is ignored
  • Interpreting
• pairs()
• pairwise ~ factors
  • Why you should avoid this
• Pairwise comparisons
  • Matrix displays
• pairwise contrasts
• Pairwise P-value plots
• params
• Percentage differences
• plot()
  • nested factors
• plot.emmGrid()
• Plots
  • of confidence intervals
  • of EMMs
  • Enhancing with ggplot2 functions
  • Interaction-style
• + operator
• Poisson regression
  • Surprising results
• polreg models
• Polynomial regression
• Pooled t
  • Instead of Welch’s t
• postGridHook
• Practices, recommended
• Precision
  • Displaying results with more digits
• Predictions
  • Bayesian models
    • in predictions: bayes
    • in sophisticated: predict-mcmc
  • Error SD
  • graphics
  • on Particular strata
  • Posterior predictive distribution
  • Reference grid
  • Total SD
• print.summary_emm()
• Probit regression
  • Odds or risk ratios
• pwpm()
• pwpp()

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Q

• qdrg()
• Quadratic terms
• Quick-start guide

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R

• R-squared
• Random predictors
  • Accessing levels
• Random slopes
  • Bias adjustment
• Rank deficiency
• Ratios
  • but I wanted differences
• rbind()
• Re-gridding
  • Implied
• Re-labeling
• Recommended practices
• recover_data()
  • Communicating with emm_basis()
  • data and params arguments
  • Dispatching
  • Error handling
  • for lqs objects
  • for rsm objects
• recover_data.call()
  • frame argument
• ref_grid()
  • at
  • cov.reduce
    • in basics: plot.emmGrid
    • in basics: RG
  • mult.name
  • nesting
  • offset
  • regrid argument
• Reference grid
  • Covariates
  • Defined
  • Indicator variables
  • Predictions on
• Reference grids
  • Prediction on
• Region of practical equivalence
• Registering recover_data and emm_basis methods
• regrid argument
• regrid()
  • probit or other non-logit models
  • regrid vs. type
  • to obtain risk ratios
  • transform = "log"
• regrid.flag
• Residual plots
• Response scale
• Response transformations
• revpairwise contrasts
• rg.limit option
• Risk ratios
• RMarkdown
• ROPE
• rsm package
• rstanarm

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S

• Sample size, displaying
• Sandwich estimators
• Satterthwaite d.f.
  • in models: K
  • in models: L
• "scale" type
• scale()
• Selecting results
• Sidak adjustment
• Significance
  • Assessing
• simple = "each"
• Simple comparisons
  • in confidence-intervals: simple
  • in FAQs: interactions
  • in interactions: simple
• Simpson’s paradox
• specs
  • Formula
• Standardized response
• stanreg objects
• * gazing (star gazing)
• Startup options
• Statistical consultants
• Statistics is hard
• str()
• submodel
  • "minimal" and "type2"
  • in a multivariate model
  • in messy-data: submodels
  • in xplanations: submodels
• Subsets of data
• summary()
  • adjust
  • in basics: emmobj
  • Bayesian models
    • in confidence-intervals: summary
    • in models: S
  • Calculated columns
  • in confidence-intervals: summary
  • HPD intervals
  • hpd.summary()
  • infer
    • in comparisons: pairwise
    • in confidence-intervals: summary
  • Show sample size
  • type = "unlink"
• summary_emm object
  • As a data frame

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T

• t tests vs. z tests
• test()
  • delta
  • joint = TRUE
• Tests
  • Equivalence
  • Non-inferiority
  • Nonzero null
  • One- and two-sided
• Too few means
• Transformations
  • Adding after the fact
  • Auto-detected
  • Back-transforming
  • Bias adjustment
  • Custom
  • faking
  • Faking a log transformation
  • Graphical display
  • with link function
  • Log
  • Overview
  • Percent difference
  • Re-gridding
  • Response versus link functions
  • scale()
  • Standardizing
  • Timing is everything
• Transformations|Implied re-gridding
• Transformations|Special modes
• Trends
  • Estimating and comparing
• trt.vs.ctrl contrasts
• Tukey adjustment
  • Ignored or changed
• type
• type = "response"
• type = "scale"
• Type II analysis
• Type III tests
  • in confidence-intervals: joint
  • in confidence-intervals: joint_tests

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U

• Unadjusted tests
• update()
  • tran
• Using results

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V

• Variables that are not predictors
• vcov.
• vcovHook
• Vignettes
  • Comparisons
  • Confidence intervals and tests
  • Explanations supplement
  • Extending emmeans
  • FAQS
  • Interactions
  • Messy data
  • Predictions
  • Sophisticated models
  • Transformations and link functions
  • Utilities and options

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W

• Weighting
  • Equal weights
• weights
• Welch’s t comparisons
  • Example
• wt.nuis

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X

• xtable method

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Z

• z tests
  • vs. t tests
• zeroinfl models

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Index generated by the vigindex package.