All Questions
3,081 questions
9
votes
1
answer
1k
views
On the use of weighted correlations in aggregated survey data
I am analyzing data from two surveys that I merged together:
School staff survey, for years 2005-06 and 2007-08
School students survey, for years 2005-06 through 2008-09
For both of these data sets, ...
- 701
13
votes
2
answers
841
views
MCMC converging to a single value?
I'm trying to fit a hierarchical model using jags, and the rjags package. My outcome variable is y, which is a sequence of bernoulli trials. I have 38 human subjects which are performing under two ...
- 2,457
6
votes
3
answers
477
views
Estimating correlated parameters with multi-level model
I would like to estimate a multi level model in Stata or R (using lmer) where the first level coefficients are the same for all observations, but the coefficients within observation are correlated.
...
- 958
4
votes
3
answers
5k
views
Stepwise model selection, Hosmer-Lemeshow statistics and prediction success of model in nested logistic regression in R
is it possible to do stepwise (direction = both) model selection in nested binary logistic regression in R? I would also appreciate if you can teach me how to get:
Hosmer-Lemeshow statitistic,
Odds ...
- 121
5
votes
1
answer
124
views
Testing for the effect of an intervention when it is applied on a group of which each individual is measured
Suppose we have 500 students nested in 20 classes (different classrooms), 25 students per class
student<-factor(1:500)
class<-rep(LETTERS[1:20],each=25)
...
- 3,191
3
votes
1
answer
128
views
Statistics of events and invitations
I am going to be hosting a number (~10) of potluck meals over the course of the summer, my pool of people to invite is about 40 people with about 10-15 coming to each meal. So I figure this would be a ...
- 133
21
votes
6
answers
13k
views
R package for multilevel structural equation modeling?
I want to test a multi-stage path model (e.g., A predicts B, B predicts C, C predicts D) where all of my variables are individual observations nested within groups. So far I've been doing this through ...
6
votes
2
answers
812
views
Possible identifiability issue in hierarchical model
I'm trying to fit some data using a hierarchical normal model
$y_i \sim N(\theta_i,\sigma^2)$
$\theta_i \sim N(\mu, \sigma_\theta^2)$
$(\mu,\sigma^2,\sigma_\theta^2) \sim diffuse$
I fit this ...
- 61
10
votes
1
answer
66k
views
How to deal with omitted dummy variables in a fixed effect model?
I am using a fixed effect model for my panel data (9 years, 1000+ obs), since my Hausman test indicates a value $(Pr>\chi^2)<0.05$. When I add dummy variables for industries that my firms ...
- 131
10
votes
3
answers
2k
views
Why the exchangeability of random variables is essential in hierarchical bayesian models?
Why the exchangeability of random variables is essential for the hierarchical Bayesian modeling?
- 3,089
4
votes
0
answers
3k
views
Panel Data: In a fixed effects model, does auto-correlation introduce bias?
Given a panel of countries over time, a fixed effects estimator makes sense to control for country-specific effects. My intuition tells me that if the dependent variable is correlated with lags of the ...
- 395
3
votes
1
answer
355
views
Predicting index from multiple predictors using panel data over 10 years: logit or probit? Fixed or random?
I am writing my master´s thesis in finance on the topic of voluntary disclosure of financial targets in annual reports of manufacturing firms.
Context
I have created a dependent variable that is an ...
- 131
46
votes
4
answers
80k
views
Standard error clustering in R (either manually or in plm)
I am trying to understand standard error "clustering" and how to execute in R (it is trivial in Stata). In R I have been unsuccessful using either plm or writing my ...
- 1,281
6
votes
2
answers
3k
views
Correct specification of longitudinal model in lme4
I am trying to fit a multilevel longitudinal model and i have a question regarding how to specify it.
The data consist of about 8k observations collected from about 3k individuals at four time points. ...
- 1,039
6
votes
2
answers
899
views
Deriving mathematical model of pLSA
After knowing how LSA works, I went on continue reading on pLSA but couldn't really make sense of the mathematical formula. This is what I get from wikipedia (other academic papers/tutorial show ...
- 207
22
votes
2
answers
836
views
Fisher information in a hierarchical model
Given the following hierarchical model,
$$
X \sim {\mathcal N}(\mu,1),
$$
and,
$$
\mu \sim {\rm Laplace}(0, c)
$$
where $\mathcal{N}(\cdot,\cdot)$ is a normal distribution. Is there a way to get an ...
- 2,099
10
votes
1
answer
6k
views
Clustered standard errors and multi-level models
Stata allows estimating clustered standard errors in models with fixed effects but not in models random effects? Why is this?
By clustered standard errors, I mean clustering as done by stata's ...
- 958
2
votes
1
answer
2k
views
Multiple imputation for clustered data
I have a few questions regarding multiple imputation for nested data.
Context: I have repeated measures (4 times) from a survey and these are clustered in workplaces (205 workplaces). There are about ...
- 1,039
25
votes
2
answers
15k
views
Why is a $p(\sigma^2)\sim\text{IG(0.001, 0.001)}$ prior on variance considered weak?
Background
One of the most commonly used weak prior on variance is the inverse-gamma with parameters $\alpha =0.001, \beta=0.001$ (Gelman 2006).
However, this distribution has a 90%CI of ...
- 7,270
25
votes
3
answers
624
views
Equations in the news: Translating a multi-level model to a general audience
The New York Times has a long comment on the 'value-added' teacher evaluation system being used to give feedback to New York City educators. The lede is the equation used to calculate the scores - ...
- 575
5
votes
2
answers
6k
views
Why do I get different heteroscedasticity robust standard errors in R when using the plm package?
I am now writing my bachelors thesis and I have come across some difficulties. I am about to do some panel regressions with time and entity fixed effects and I would therefore like to use the plm ...
- 81
4
votes
2
answers
7k
views
Evaluating effect sizes of interactions in multiple regression
I have been running 3-level multilevel models with HLM, and my main interest is in some cross-level interaction effects that I am finding. My concern is that the effect sizes of these interactions ...
user2686
15
votes
3
answers
5k
views
Removing factors from a 3-way ANOVA table
In a recent paper, I fitted a three-way fixed effects model. Since one of the factors wasn't significant (p > 0.1), I removed it and refitted the model with two fixed effects and an interaction.
I'...
- 12.9k
5
votes
1
answer
3k
views
Multi-stage selection model with panel data in R
My data consists of individual level observations nested within countries over time. I would like to use multilevel models along with some sort of selection model.
I have three related questions.
...
- 285
10
votes
4
answers
9k
views
How to test random effects in a multilevel model in R
I have been reading a good book called Applied Longitudinal Data Analysis: Modeling Change and Event Occurrence by Judith Singer and John Willet. The book shows that by modeling in 2 levels, we can ...
- 517
440
votes
9
answers
893k
views
What is the difference between fixed effect, random effect in mixed effect models?
In simple terms, how would you explain (perhaps with simple examples) the difference between fixed effect, random effect in mixed effect models?
- 6,318
41
votes
3
answers
10k
views
What's the relation between hierarchical models, neural networks, graphical models, bayesian networks?
They all seem to represent random variables by the nodes and (in)dependence via the (possibly directed) edges. I'm esp interested in a bayesian's point-of-view.
- 812
5
votes
4
answers
552
views
Are these equivalent representations of the same hierarchical Bayesian model?
If $X$ is a categorical variable, and I am interested in the posterior distributions of $\beta_1$, where $\beta_1$ is a vector of coefficients, one for each level of X, are these equivalent models?
...
- 7,270
4
votes
3
answers
278
views
What is a good internet based source of information on Hierarchical Modeling?
I am talking about the regression method that measures the impact of several layers of independent variables upon a dependent variable.
- 7,882
7
votes
2
answers
2k
views
Combining repeated experiments into one dataset
I hope you all won't mind a basic question.
We are examining the effects of a compound at various concentration on the behaviour of an organism. The compound is administered once at the beginning of ...
- 397
42
votes
8
answers
26k
views
Under what conditions should one use multilevel/hierarchical analysis?
Under which conditions should someone consider using multilevel/hierarchical analysis as opposed to more basic/traditional analyses (e.g., ANOVA, OLS regression, etc.)? Are there any situations in ...
- 783