meta user
network profile
| bio | website | |
|---|---|---|
| location | ||
| age | ||
| visits | member for | 1 year, 6 months |
| seen | Jan 13 at 2:59 | |
| stats | profile views | 134 |
|
Feb 16 |
comment |
Treatment of interactions in multiple regression rolando2, test of significance are not designed to tell you whether covariates "merit" being in the model. They tell you whether associations adjusted for other factors are beyond chance; this is not the same thing, particularly with collinear covariates. |
|
Feb 16 |
comment |
How to create a loop without command “for” in Bugs? If you want to forward sample data, just add a new node to the model. See the "y.new" node here; classes.soe.ucsc.edu/ams206/Winter03/h34m18.pdf This idea is used a lot in posterior predictive checks; see use of "y.rep" here; stat.columbia.edu/~gelman/presentations/ggr2handout.pdf |
|
Feb 14 |
comment |
Test for significance with no comparator What do you mean by "significant"? For example, what hypothesis would you reject, when you found a feature to be significant? Without this I don't think we can help, beyond suggesting simple summaries. |
|
Feb 14 |
answered | How to create a loop without command “for” in Bugs? |
|
Feb 12 |
comment |
Does the link function in a GLM influence the plot of residuals? It's unusual for the choice of link function to matter much, when fitting GLMs - this is effectively what the Li-Duan theorem says. |
|
Feb 7 |
comment |
Fixed-effects or mixed-effects models to population based data If the countries are exchangeable, or conditionally exchangeable you have (by de Finetti's theorem) an argument for using some random effects approach, regardless of how you sampled the data. Which random effects approach to use is a much more difficult question, however. |
|
Jan 29 |
awarded | Necromancer |
|
Jan 27 |
answered | Do expits reveal effect sizes with logistic regression? |
|
Jan 25 |
comment |
What is the difference between GLM and GEE? Do you really want to fit subject id as a continuous covariate? It seems strange to have the response variable be an increasing or decreasing function of id. |
|
Jan 25 |
awarded | Excavator |
|
Jan 25 |
revised |
What is the best introductory Bayesian statistics textbook? Included author name - there are lots of similarly-titled books in this list, author names help distinguish them |
|
Jan 25 |
comment |
Without multi-level modeling, how to handle within-study replication in a meta-analysis, where the study is the unit of replication? You're right, it is a problem. Not so much with the point estimates, but the measures of precision (i.e. standard errors) will be too small; it ignores the multiple use of the control group's data. It shouldn't however, be news to anyone in meta-analysis. The Kim/Becker article above is basically a re-statement -with acknowledgement- of Gleser & Olkin (1994). Stochastically dependent effect sizes. In Cooper & Hedges (Eds), The handbook of research synthesis (pp. 339–355). This book is a standard text in the field, I believe now in a second edition. |
|
Jan 24 |
comment |
Bootstrapping estimates of out-of-sample error This form of bootstrapping isn't guaranteed to work. If the true predictive ability of the model is zero, then you don't get asymptotic normality of the quantity being bootstrapped, and the bootstrap confidence intervals above are not valid confidence intervals. With close to zero predictive ability, in finite sample sizes you still get badly-miscalibrated intervals. |
|
Jan 24 |
comment |
How to test for and deal with regression toward the mean? It's not clear what the treatment is here, and in particular when and why it was administered. Could you tell us please? To compare mean IV levels at times and 2, you could just compute the average differences in IV, comparing time 2 to time 1. Assuming the IVs are independent for each person, this gives a measure of improvement; test its significance with a one sample t-test, if you like. But this analysis doesn't say anything about treatment, which is what you're interested in. |
|
Jan 24 |
comment |
How can I calculate a critical t value using R? The qt() function does this. |
|
Jan 24 |
comment |
Without multi-level modeling, how to handle within-study replication in a meta-analysis, where the study is the unit of replication? Is the meta-analysis really just averaging all these difference values of R? That seems rather strange, compared to e.g. attempting a meta-regression - in which case the differences between R at different levels of X might be what you're interested in combining across studies. |
|
Jan 24 |
comment |
My groups differ on covariate We need a little more information to help you. What defines the groups? Is this a randomized study? What do you mean by "needing" a p-value above 0.05? |
|
Jan 20 |
comment |
What sense does it make to compare p-values to each other? What's the outcome you measured? (i.e. what is it that differs, between the groups defined by A/not A, or B/not B?) Is it measured on all 1000 samples, or are some missing? |
|
Jan 19 |
answered | Deriving ${\rm var}(\overline{X})$ from expected value definition |
|
Jan 19 |
answered | R code for estimating a Poisson parameter and its CI? |
