All Questions
Tagged with multivariate-testing glm
7 questions
1
vote
1
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57
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mvabund fourth corner model using categorical environmental levels
Within mvabund::traitglm() is it appropriate to use a categorical R matrix rather than continuous environmental variables? I am interested in the effect of the interaction between MHW period (before, ...
- 145
1
vote
0
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106
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Can `mvabund::traitglm()` handle random effects?
I am using the R package mvabund to examine how environmental conditions and species traits are correlated with ecological community structure. The traitglm() function is a nice tool for this. However,...
- 145
1
vote
1
answer
92
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Multiple Outcome Binomial Regression R
It is possible to use cbind to specify multiple outcomes for plain lm regressions as such:
set.seed(11)
df <- iris %>%
mutate(var1 = sample(c(0L,1L), 150, replace = TRUE),
var2 = ...
- 2,997
3
votes
1
answer
573
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Error/warning on running glm in R - Coefficients: (1 not defined because of singularities)
When I run this glm on model_df (dput below):
model <- glm(outcome_variable_data ~ ., data = model_df, family = 'binomial')
lrm <- summary(model)
When I print lrm, I get the error:
Coefficients: ...
- 326
0
votes
1
answer
104
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Error code: must have identical levels in the same order
When running the MCMCglmm function I get the following error message:
fit_mcmc <- MCMCglmm(exchange ~ assocSRI,random=~mm(ID1 + ID2), data=within_dyad)
Error in buildZ(rmodel.terms[r], data = data,...
-1
votes
1
answer
407
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multiple GLMs in a for loop
I am looking to estimate parameters for a large set (274) of correlated response variables which follow a NB dist. The goal is to use the parameters for a generalized linear model for each of the ...
- 1
1
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1
answer
690
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What statistic method to use in multivariate abundance data with random effects?
I am working with multivariate data with random effects.
My hypothesis is this: D has an effect on A1 and A2, where A1 and A2 are binary data, and D is a continuous variable.
I also have a random ...
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