Linked Questions

Here is how I have understood nested vs. crossed random effects: Nested random effects occur when a lower level factor appears only within a particular level of an upper level factor. For example,...

Linear Mixed Effects Models are Extensions of Linear Regression models for data that are collected and summarized in groups. The key advantages is the coefficients can vary with respect to one or more ...

I understand that the difference between them is related to whether the grouping variable in the model is estimated as a fixed or random effect, but it's not clear to me why they are not the same (if ...

I am analyzing data on "BloodSugar" level (dependent variable) and trying to find its relation with "age", "gender" and "weight" (independent variables) of ...

In Bayesian multilevel models (with, say, people nested within congressional districts) I sometimes see individual level demographic variables like race modeled as random effects. So here’s a slightly ...

Now I'm having a hard time having a grasp on the difference between fixed and random effects of regression models. I believe I understand it's recommended to use random effects if you consider ...

I am trying to fit a mixed model with about 45 groups, about 10 of the groups have just one observation and about 10 groups have more than 5 observations. The total number of observations is around ...

I have a model M calculated via lme4's glmer function, with random effects ("Customer ID") and fixed effects for each customer ID. My dataset is very large, so I would like to select a sample of ...

Here is somewhat simplified structure of the data I have, since fixed effects are quite straight forward, however, random effects are giving me a headache (like I said something new :) ): ...

What are the difference between a linear mixed model with random slope and intercept and a linear model with an interaction effect? If I predict the effect of 1) the main effect and 2) the random ...

I understand that fixed vs. random effects have different meaning whether it be in biostatistics or econometrics. I recently came across a talk regarding fixed vs. random effects in the hierarchical ...

I have been reading about experimental design, and Randomized Complete Block designs (RCBD) in particular and I have a few queries. What exactly is a randomized complete block design ? Is there a ...

I am performing a meta-regression of nine studies that look at cancer risk vs level of substance in the drinking water. Each study has a reference strata and one to five higher strata. The studies ...

I have a sample of 20 subjects. I have two continuous variables, X and Y which are linearly related. I use linear regression to estimate the regression coefficient relating X and Y. For each subject, ...

I'm faced with analyzing the following design: In a longitudinal study, the muscle tissue of about 25 subjects are analyzed at 8 timepoints. Specifically, 7 measurements are taken during a race ...