benwhalley

<?xml version="1.0" ?>
 <auth>
     <publications>
         <publication>
             <authors>bjwhalley,thollins</authors>
             <elements_id>1</elements_id>
             <bibtex>{Stuff here}</bibtex>
             <timestamp>2050-01-31T20:00-4:00</timestamp>
         </publication>
         <publication>

benwhalley

library(rstanarm)
library(tidybayes)
m1 <- stan_lmer(t2_accuracy ~ lag*condition + (1|p), data = rsvp_accuracy)

nd <- expand.grid(condition=unique(rsvp_accuracy$condition), lag=factor(c(1,3))) %>% as.tibble() %>% mutate(p=Inf)

m1.preds <- add_fitted_samples(nd, m1)
m1.preds.wide <- m1.preds %>% 
  data.table::dcast(.iteration+condition~lag) 

benwhalley

benwhalley

benwhalley

```{r}
expand.grid(person=1:5, trial=1:10) %>% 
  group_by(person) %>% 
  mutate(trialnumcreate = row_number()) %>% 
  ungroup() %>% 
  arrange(person,trial)
  

mtcars %>% 

benwhalley

 [1] "3. Age"                                                                                                                                                                      
 [2] "4. Gender"                                                                                                                                                                   
 [3] "5. Height (cm eg, 168)"                                                                                                                                                      
 [4] "6. Current Weight (kg eg, 66)"                                                                                                                                               
 [5] "7. The lowest adult weight that you have ever been from age of 18 onwards (kg eg, 50)"                                                                                       
 [6] "8. Highest adult weight that you have ever been since the age of 18, excluding pregnancy (kg eg, 62)"                 

benwhalley

@article{henderson_stepwise_1989,
    title = {Stepwise {Regression} in {Social} and {Psychological} {Research}},
    volume = {64},
    issn = {0033-2941},
    url = {https://doi.org/10.2466/pr0.1989.64.1.251},
    doi = {10.2466/pr0.1989.64.1.251},
    abstract = {Researchers often invoke stepwise ordinary least squares regression to explain, predict or classify practical problems or theoretical constructs in psychological and social research. Unfortunately, this statistical technique is used without proper consideration for its inherent theoretical and practical limitations, a problem expected to grow even more serious with the proliferation of statistical packages for use on personal computers. Use of stepwise regression in social and psychological research is reconsidered here. Explanations of forward selection, backward elimination and combination stepwise procedures are provided; limitations of the technique, statistical and practical, are then addressed. Analysis shows that most of the current applic

benwhalley

Presenting: https://www.youtube.com/watch?v=1RwJbhkCA58&start=118&end=190

Design process: https://www.youtube.com/watch?v=1RwJbhkCA58&start=364&end=600

Ideal poster goals: https://www.youtube.com/watch?v=1RwJbhkCA58&start=645&end=690

Final design:

benwhalley

import random
import pandas as pd

def randomisesims():
    stimA = list(range(1,91))
    stimB = list(range(91,131))
    random.shuffle(stimA)
    random.shuffle(stimB)
    return stimA[:40]+stimB[:20]

benwhalley