variance components

1. difference between estimating variance and standard deviation.

In a simulation study, is there any difference between \bullet to estimate the variance \sigma^2, 1000 times and taking its average, and \bullet to estimate the standard deviation \sigma, 1000 times and taking its average? Can I do anyone of these? Is there any preference of doing a...
2. Degrees of Freedom for linear combination of VarianceComponents

I was trying to figure out satterthwaite's degrees of freedom for the combination of variance component to calculate confidence interval. I can get the confidence interval for individual variances using lme4 package in R. I am interested in calculating confidence interval for combination of...
3. Creating standard normal distribution with difference variances within quartiles

Hi, I have 10,000 data points referring to data on dogs that follow a positively skewed distribution that I have grouped into quartiles. I would a second distribution (highly correlated with the first distribution) associated with the same set of dogs whereby the distribution represents a...
4. Systematic component variation

The appendix of the paper of [McPherson et al (1982) contains a derivation of the systematic component variation SCV. I understand the derivation with exception of the first step. Here are the premisses: O_i: observed cases in region i E_i: expected cases in region i \lambda_i...
5. Simple Algebraic Calculation about underestimation

In a findings, it is found that the non-coverage rate for the second-level intercept variance is 8.9%, and the non-coverage rate for the second-level slope variance is 8.8%. Although the coverage is not grotesquely wrong, the 95% confidence interval is clearly too short. The amount of...
6. How is the confidence interval for variance component in "lmer" function computed ?

Here is the R code : library(lme4) fm1 <- lmer(Reaction ~ Days + (Days | Subject), sleepstudy) confint.merMod(fm1,oldNames=FALSE) And the output is 2.5 % 97.5 % sd_(Intercept)|Subject 14.3814761 37.715996...
7. Interpretation of various output of "lmer" function in R

library(lme4) fm1 <- lmer(Reaction ~ Days + (Days | Subject), sleepstudy) The notation (Days | Subject) says to allow the intercept and Days to vary randomly for each level of Subject . Can you please explain me the result of the following commands ...
8. Confidence interval of parameters of mixed-model in R

Hi , can anyone please explain me the following output produces in R when I ran the command confint(lmer()) . Here is the R code : library(lme4) fm1 <- lmer(Reaction ~ Days + (Days | Subject), sleepstudy) confint(fm1) And the output is : Computing profile confidence...
9. Explaining different process variances

Hi everybody, The situation: I'm stuck with the following problem: some measurements are done on a number of batches. These measurements are assays and are done on a number of batches giving different concentrations, batch concentration. The assays themselves also produced control...
10. G Theory / Variance Components problems

I'm running SPSS Variance Components analyses using REML estimation. I have both real and fictitious data in which employees are rated by multiple raters. Subject ID and Rater ID are both treated as random. On both real and fictitious data, the main effects seem to work ok. However, when I...
11. Factor Analysis

Hello! I run a Factor Analysis and got 14 factors with an Eigenvalue above 1! The first 5 factors explain most of the variance (Eigenvalue >2) and the remaining 9 factors have an eigenvalue around 1.5 What shall I do? Shall I keep all 14 factors or extract only the first 5 that explain...
12. Variance Components and Intraclass Correlation Coefficients for Binary Data

Hi, I am performing a variance components analysis of a 3 level nested model of binary data. Given the lack of homoscedasticity at the individual data, how do I calculate ICCs?