この節の作者: Ravi Selker, Jonathon Love, Damian Dropmann

Log-Linear Regression (logLinear)

Description

Log-Linear Regression

Usage

logLinear(
  data,
  factors = NULL,
  counts = NULL,
  blocks = list(list()),
  refLevels = NULL,
  modelTest = FALSE,
  dev = TRUE,
  aic = TRUE,
  bic = FALSE,
  pseudoR2 = list("r2mf"),
  omni = FALSE,
  ci = FALSE,
  ciWidth = 95,
  RR = FALSE,
  ciRR = FALSE,
  ciWidthRR = 95,
  emMeans = list(list()),
  ciEmm = TRUE,
  ciWidthEmm = 95,
  emmPlots = TRUE,
  emmTables = FALSE,
  emmWeights = TRUE
)

Arguments

data	the data as a data frame
factors	a vector of strings naming the factors from data
counts	a string naming a variable in data containing counts, or NULL if each row represents a single observation
blocks	a list containing vectors of strings that name the predictors that are added to the model. The elements are added to the model according to their order in the list
refLevels	a list of lists specifying reference levels of the dependent variable and all the factors
modelTest	TRUE or FALSE (default), provide the model comparison between the models and the NULL model
dev	TRUE (default) or FALSE, provide the deviance (or -2LogLikelihood) for the models
aic	TRUE (default) or FALSE, provide Aikaike's Information Criterion (AIC) for the models
bic	TRUE or FALSE (default), provide Bayesian Information Criterion (BIC) for the models
pseudoR2	one or more of 'r2mf', 'r2cs', or 'r2n'; use McFadden's, Cox & Snell, and Nagelkerke pseudo-R², respectively
omni	TRUE or FALSE (default), provide the omnibus likelihood ratio tests for the predictors
ci	TRUE or FALSE (default), provide a confidence interval for the model coefficient estimates
ciWidth	a number between 50 and 99.9 (default: 95) specifying the confidence interval width
RR	TRUE or FALSE (default), provide the exponential of the log-rate ratio estimate, or the rate ratio estimate
ciRR	TRUE or FALSE (default), provide a confidence interval for the model coefficient rate ratio estimates
ciWidthRR	a number between 50 and 99.9 (default: 95) specifying the confidence interval width
emMeans	a list of lists specifying the variables for which the estimated marginal means need to be calculate. Supports up to three variables per term.
ciEmm	TRUE (default) or FALSE, provide a confidence interval for the estimated marginal means
ciWidthEmm	a number between 50 and 99.9 (default: 95) specifying the confidence interval width for the estimated marginal means
emmPlots	TRUE (default) or FALSE, provide estimated marginal means plots
emmTables	TRUE or FALSE (default), provide estimated marginal means tables
emmWeights	TRUE (default) or FALSE, weigh each cell equally or weigh them according to the cell frequency

Output

A results object containing:

results$modelFit	a table
results$modelComp	a table
results$models	an array of model specific results

Tables can be converted to data frames with asDF or as.data.frame(). For example:

results$modelFit$asDF

as.data.frame(results$modelFit)

Examples

data('mtcars')

tab <- table('gear'=mtcars$gear, 'cyl'=mtcars$cyl)
dat <- as.data.frame(tab)

logLinear(data = dat, factors = vars(gear, cyl),  counts = Freq,
          blocks = list(list("gear", "cyl", c("gear", "cyl"))),
          refLevels = list(
              list(var="gear", ref="3"),
              list(var="cyl", ref="4")))

#
#  LOG-LINEAR REGRESSION
#
#  Model Fit Measures
#  ---------------------------------------
#    Model    Deviance    AIC     R²-McF
#  ---------------------------------------
#        1    4.12e-10    41.4     1.000
#  ---------------------------------------
#
#
#  MODEL SPECIFIC RESULTS
#
#  MODEL 1
#
#  Model Coefficients
#  ------------------------------------------------------------------
#    Predictor          Estimate     SE          Z            p
#  ------------------------------------------------------------------
#    Intercept          -4.71e-16        1.00    -4.71e-16    1.000
#    gear:
#    4 – 3                  2.079        1.06        1.961    0.050
#    5 – 3                  0.693        1.22        0.566    0.571
#    cyl:
#    6 – 4                  0.693        1.22        0.566    0.571
#    8 – 4                  2.485        1.04        2.387    0.017
#    gear:cyl:
#    (4 – 3):(6 – 4)       -1.386        1.37       -1.012    0.311
#    (5 – 3):(6 – 4)       -1.386        1.73       -0.800    0.423
#    (4 – 3):(8 – 4)      -26.867    42247.17    -6.36e -4    0.999
#    (5 – 3):(8 – 4)       -2.485        1.44       -1.722    0.085
#  ------------------------------------------------------------------
#