对于某些人来说，是否有可能改变这段代码以允许随机效应( jmv包中的logRegBin函数)

Question

对于某些人来说，是否有可能改变这段代码，以便在二项式回归模型中允许随机效应。这是运行二项逻辑回归(来自jmv包的logRegBin函数)的代码，但它不允许随机效应。

overview.html

R文件

logRegBin {jmv} R Documentation
Binomial Logistic Regression
Description
Binomial Logistic Regression

Usage
logRegBin(data, dep, covs = NULL, factors = NULL,
  blocks = list(list()), refLevels = NULL, modelTest = FALSE,
  dev = TRUE, aic = TRUE, bic = FALSE, pseudoR2 = list("r2mf"),
  omni = FALSE, ci = FALSE, ciWidth = 95, OR = FALSE,
  ciOR = FALSE, ciWidthOR = 95, emMeans = list(list()),
  ciEmm = TRUE, ciWidthEmm = 95, emmPlots = TRUE,
  emmTables = FALSE, emmWeights = TRUE, class = FALSE, acc = FALSE,
  spec = FALSE, sens = FALSE, auc = FALSE, rocPlot = FALSE,
  cutOff = 0.5, cutOffPlot = FALSE, collin = FALSE,
  boxTidwell = FALSE, cooks = FALSE)
Arguments
data    
the data as a data frame

dep 
a string naming the dependent variable from data, variable must be a factor

covs    
a vector of strings naming the covariates from data

factors 
a vector of strings naming the fixed factors from data

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

OR  
TRUE or FALSE (default), provide the exponential of the log-odds ratio estimate, or the odds ratio estimate

ciOR    
TRUE or FALSE (default), provide a confidence interval for the model coefficient odds ratio estimates

ciWidthOR   
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

class   
TRUE or FALSE (default), provide a predicted classification table (or confusion matrix)

acc 
TRUE or FALSE (default), provide the predicted accuracy of outcomes grouped by the cut-off value

spec    
TRUE or FALSE (default), provide the predicted specificity of outcomes grouped by the cut-off value

sens    
TRUE or FALSE (default), provide the predicted sensitivity of outcomes grouped by the cut-off value

auc 
TRUE or FALSE (default), provide the rea under the ROC curve (AUC)

rocPlot 
TRUE or FALSE (default), provide a ROC curve plot

cutOff  
TRUE or FALSE (default), set a cut-off used for the predictions

cutOffPlot  
TRUE or FALSE (default), provide a cut-off plot

collin  
TRUE or FALSE (default), provide VIF and tolerence collinearity statistics

boxTidwell  
TRUE or FALSE (default), provide Box-Tidwell test for linearity of the logit

cooks   
TRUE or FALSE (default), provide summary statistics for the Cook's distance

Answer 1

几乎可以肯定不是；添加随机效应并不简单！

由于您正在使用jmv，所以您可能对Jamovi的GAMLj模块感兴趣，例如这里。该模块构建在lme4包上；我认为在jmv中没有类似的函数向R中的GLMMs公开更友好的用户界面，您可以尝试ez包，特别是ezMixed函数.