Hi all,
I hope this question is appropriate here, apologies if not.
I’m trying to run dyadic multi-membership brms models in R, where one the predictors is a categorical variable, coded as a factor, with multiple levels. Every time I’ve run these kinds of models in the past, the summary(model) output for categorical factors is the reference factor level comparison to to every other factor level; e.g. FactorNameLevelABC - Estimate, CI, etc
This time around, it seems that each factor level is being assigned a number rather than retaining its name So I’m getting FactorName1, FactorName2, FactorName3; meaning I can’t be 100% sure of what factor level is being compared against each of the others. (I’m assuming it is the first factor level encountered is the reference, the second encountered being FactorName1, etc).
I’ve tried renaming the factor levels so they only have letters in their names (no symbols), re-classified them as characters, running the model without the multi-membership term.
I have limited experience running stan/brms in R, so hopefully I’m not overlooking something very basic!
Heres some dummy code to explain the problem
levels(data$categoral_variable)
"apple" "banana" "orange" "berry"
model <- brm(dissimilarity_matrix ~ continuous_variable + categorical_variable + (1|mm(IDA,IDB)) + data = data,
family= "Gaussian",
warmup = 10, iter = 40,
cores = 2, chains = 4,
init=0)
summary(model)
Regression Coefficients:
Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS
Intercept 0.0 0.0 -1.0 0.0 Inf 6 NA
continous_variable -0.00 0.00 -0.00 0.00 Inf 6 NA
categorial_variable1 0.00 0.00 -0.00 0.00 Inf 6 NA
categorial_variable2 -0.00 0.00 -0.00 0.00 Inf 6 NA
categorial_variable3 0.00 0.00 -0.00 0.00 Inf 6 NA
whereas what I was expecting was:
summary(model)
Regression Coefficients:
Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS
Intercept 0.18 0.95 -1.44 0.88 Inf 6 NA
continous_variable -0.00 0.00 -0.00 0.00 Inf 6 NA
categorial_variablebanana 0.00 0.00 -0.00 0.00 Inf 6 NA
categorial_variableorgange -0.00 0.00 -0.00 0.00 Inf 6 NA
categorial_variableberry 0.00 0.00 -0.00 0.00 Inf 6 NA
Thank you very much in advance!