0 Feedback 945 Assignment2
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General Fe edback on Psyc9 45 Ass ignme nt 2 1. This wen t well for the most p a r t , a lt hou g h se v e r al folks for g o t t o g ive fo r mulas for p seudo -R 2 and ran dom effects con fide nce interva ls. Form ulas will be e as ier to und ers tan d tha n text, but thepoint i s that many people will not familiar with these things and so they should be explained explicitly. 2. Th e reasons w h y ANOVA w ouldn’t w ork he r e should be desc r ibe d in t he con t ext of t he cu r r ent stu dy. I n orde r to explain why eithe r A NOVA won ’t work, you’d wa nt to de scribe wh a t ge ts ag greg ate d over to us e ANOVA, and wh y this is a p roblem . Y ou’d wa nt to note wha t com prom ise s are req ui red i n terms of how pre di ctor effects can b e sp ecified , as we ll as wh at kinds of res ea rch que stions ANOV A does n’t a ddres s. One m ight a lso com m ent ab out a ssum ptions re ga rding m issi ng da ta within ea ch approa ch. 3. No bi g probl em s he re. Make sure to interpret the randomeffects con fide nce intervals for the re ade r, as they a re not your typical conf ide nce interval around a point e stim ate . 4 . Everyone g ot the m ain ef fect correct, but m ake s ure to provide e ffect size (vi a ps eu do-R 2 ) for each effect , i ndicating wh ich va rian ce it accoun ted for. A lso re port the de vian ce d ifference te st for answer the la st qu es tion. I ha d a sked for thes e e ffe cts se que nti all y i n orde r to facil itat e com puta tion of effect size, so it will be helpful to all of us if you build the model sequentially as well. 5. Sam e a s # 5, except to m ake sure to include a nd inte rpret the eff ect size of the ran dom s lope varian ce (via a random effect confidence interval). 6. Even thou gh the inte raction was non -si gnifican t, an effe ct size is s till warran ted . I n g en era l, this is how you distinguish between situations of low power versus an actual non-practically-significant effect. Please report and interpret the coefficient as well (for practice, at the very least). 7. Makesure to rep ort the de vian ce d iffere nce te st for this and clea rly ide nti fy which varian ce compone nt expres se s this idea , as wel l as wha t this result mea ns conce ptua lly. 8. The r e were a t otal of 4 IQ effec t s t o b e r epor t ed, each o f which has an e ffe ct size. Y o u can add t hem all at on ce, but p lease be clea r about which e ffects were a dde d so that I will know how ea ch shou ld be interpreted (i.e., what is conditional and what is not). These effects target different variance comp onen ts. I f you are n ot sure which e ffects ta rget whi ch varian ce, try add ing the m one a t a ti m e s o you can se e what happens. Make su re to report and interpret the i ntera ctions a s wel l. 9. Y ou are allowed t o dro p nons ig nifican t e ffe c t s that a r e no t needed for p ro p er in t e r p r eta t ion t o make this part ea si er. Whe n noting the overall m ode l R 2 , please explain how this was calculated, as it was done differen tly than the other ps eud o-R 2 calculations. 1 0 . Th e in st r uc t io ns t o ld y ou w h at va lu e s o f t h e pr e d ic t o r s t o b e p lo t t e d , b ut ma k e su r e y ou r emem b er t h e pre di ctors a re ce nte red (e spe ciall y I Q). I n the te xt you sh oul d de scribe wha t “low” and “high” IQ actually means, as well as what this plot indicates conceptually (i.e., what is the pattern in English). Hope tha t hel ps! As al ways, please com e se e me or em ail m e to go over any ques tions you have. Le sa
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General Feedback on Psyc945 Assignment 2
1. This went well for the most part, although several folks forgot to give formulas for pseudo-R2 andrandom effects confidence intervals. Formulas will be easier to understand than text, but the point is
that many people will not familiar with these things and so they should be explained explicitly.
2. The reasons why ANOVA wouldn’t work here should be described in the context of the currentstudy. In order to explain why either ANOVA won’t work, you’d want to describe what getsaggregated over to use ANOVA, and why this is a problem. Y ou’d want to note what compromisesare required in terms of how predictor effects can be specified, as well as what kinds of researchquestions ANOVA doesn’t address. One might also comment about assumptions regarding missingdata within each approach.
3. No big problems here. Make sure to interpret the random effects confidence intervals for the reader,as they are not your typical confidence interval around a point estimate.
4. Everyone got the main effect correct, but make sure to provide effect size (via pseudo-R2
) for eacheffect, indicating which variance it accounted for. Also report the deviance difference test for answerthe last question. I had asked for these effects sequentially in order to facilitate computation of effectsize, so it will be helpful to all of us if you build the model sequentially as well.
5. Same as #5, except to make sure to include and interpret the effect size of the random slope variance(via a random effect confidence interval).
6. Even though the interaction was non-significant, an effect size is still warranted. In general, this ishow you distinguish between situations of low power versus an actual non-practically-significanteffect. Please report and interpret the coefficient as well (for practice, at the very least).
7.
Make sure to report the deviance difference test for this and clearly identify which variancecomponent expresses this idea, as well as what this result means conceptually.
8. There were a total of 4 IQ effects to be reported, each of which has an effect size. You can add themall at once, but please be clear about which effects were added so that I will know how each should beinterpreted (i.e., what is conditional and what is not). These effects target different variancecomponents. If you are not sure which effects target which variance, try adding them one at a time soyou can see what happens. Make sure to report and interpret the interactions as well.
9. You are allowed to drop nonsignificant effects that are not needed for proper interpretation to makethis part easier. When noting the overall model R2, please explain how this was calculated, as it wasdone differently than the other pseudo-R2 calculations.
10. The instructions told you what values of the predictors to be plotted, but make sure you remember thepredictors are centered (especially IQ). In the text you should describe what “low” and “high” IQactually means, as well as what this plot indicates conceptually (i.e., what is the pattern in English).
Hope that helps! As always, please come see me or email me to go over any questions you have.Lesa
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