Shravan Vasishth vasishth
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| data { | |
| int<lower=1> N; | |
| real rt[N]; //outcome | |
| real c1[N]; //predictor | |
| real c2[N]; //predictor | |
| real c3[N]; //predictor | |
| int<lower=1> I; //number of subjects | |
| int<lower=1, upper=I> id[N]; //subject id | |
| vector[4] mu_prior; //vector of zeros passed in from R | |
| } |
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| Details: | |
| key: | |
| beta[1] = Intercept | |
| beta[2] = c1 | |
| beta[3] = c2 | |
| beta[4] = c3 | |
| 1. Fixed effects, Stan vs lmer: | |
| Stan: |
vasishth
/ gist:7879095
Created
December 9, 2013 19:18
Hierarchical linear model (varying intercepts model) with t distribution instead of normal
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| model | |
| { | |
| # The model for each observational unit | |
| # (each row is a subject's data point) | |
| for( j in 1:N ) | |
| { | |
| mu[j] <- beta[1] + beta[2] * ( so[j] ) + u[subj[j]] + w[item[j]] | |
| rt[j] ~ dnorm( mu[j], tau.e ) | |
| ##change the above line to: | |
| #rt[j] ~ dt(mu[j],tau.e, 2) |
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| newcomb <- | |
| c(28,26,33,24,34,-44,27,16,40,-2, | |
| 29,22,24,21,25,30,23,29,31,19, | |
| 24,20,36,32,36,28,25,21,28,29, | |
| 37,25,28,26,30,32,36,26,30,22, | |
| 36,23,27,27,28,27,31,27,26,33, | |
| 26,32,32,24,39,28,24,25,32,25, | |
| 29,27,28,29,16,23) | |
| # Data as a list |
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| > # Calculate the predicted random effects by hand for the ergoStool data | |
| > (fm1<-lmer(effort~Type-1 + (1|Subject),ergoStool)) | |
| Linear mixed model fit by REML | |
| Formula: effort ~ Type - 1 + (1 | Subject) | |
| Data: ergoStool | |
| AIC BIC logLik deviance REMLdev | |
| 133 143 -60.6 122 121 | |
| Random effects: | |
| Groups Name Variance Std.Dev. | |
| Subject (Intercept) 1.78 1.33 |
vasishth
/ corr_fixedef_lm.R
Last active
December 15, 2015 00:28
linear model correlations of fixed effects
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| > summary(lm<-lm(wear~material-1,BHHshoes)) | |
| > X<-model.matrix(lm) | |
| > 2.49^2*solve(t(X)%*%X) | |
| materialA materialB | |
| materialA 0.62001 0.00000 | |
| materialB 0.00000 0.62001 |
vasishth
/ corr_fixedeff_example2.R
Created
March 15, 2013 19:50
Calculating correlations of fixed effects in LMEs
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| > b1.vals<-subset(BHHshoes,material=="A")$wear | |
| > b2.vals<-subset(BHHshoes,material=="B")$wear | |
| > | |
| > vcovmatrix<-var(cbind(b1.vals,b2.vals)) | |
| > | |
| > covar<-vcovmatrix[1,2] | |
| > sds<-sqrt(diag(vcovmatrix)) | |
| > covar/(sds[1]*sds[2]) | |
| b1.vals | |
| 0.98823 |
vasishth
/ corr_fixedeff_example1.R
Created
March 15, 2013 19:48
Example of correlations of fixed effects
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| > (lm.full<-lmer(wear~material-1+(1|Subject), data = BHHshoes)) | |
| Linear mixed model fit by REML | |
| Formula: wear ~ material - 1 + (1 | Subject) | |
| Data: BHHshoes | |
| AIC BIC logLik deviance REMLdev | |
| 62.9 66.9 -27.5 53.8 54.9 | |
| Random effects: | |
| Groups Name Variance Std.Dev. | |
| Subject (Intercept) 6.1009 2.470 | |
| Residual 0.0749 0.274 |
NewerOlder