Exam (elaborations)
PSYC 426 Final Exam Questions and answers | Psychometrics & Individual Differences (Alex Morin)
PSYC 426 Final Exam Questions and answers | Psychometrics & Individual Differences (Alex Morin)
[Show more]
Preview 3 out of 20 pages
Uploaded on
July 22, 2024
Number of pages
20
Written in
2023/2024
Type
Exam (elaborations)
Contains
Questions & answers
Institution
PSYC 426
Course
PSYC 426
$10.49
Also available in package deal from $13.49
100% satisfaction guarantee
Immediately available after payment
Both online and in PDF
No strings attached
Also available in package deal (1)
1. Exam (elaborations) - Psyc 426 athabasca university final exam newest 2024/25
2. Exam (elaborations) - Psyc 426 athabasca university final exam with all comprehensive study set of all unit...
3. Exam (elaborations) - Psyc 426 final actual exam questions and answers | updated
4. Exam (elaborations) - Psyc 426 final exam questions and answers | psychometrics & individual differences (a...
Show more
PSYC 426 Final Exam Questions and answers | Psychometrics & Individual Differences (Alex Morin ) Bias The iipresence iiof iia iisystematic iidifference iiin iithe iiestimation iiof iiscores iion iia iigiven iiconstruct ii(i.e. iivalidity ) iifor iia iigiven iigroup **Systematic iierror ii= iivalidity, iiTHUS iibias iiis iiabout iithe iidifference iiin iiterms iiof iivalidity Some iitests iimight iibe iibiased iifor iimembers iiof iispecific iicultural ii(or iiother) iigroups Whats iithe iidifference iibetween iibias iiand iimargin iiof iierror? Margin iiof iierror iiis iiabout iirandom iimeasurement iierror ii (Every iitest iicontains iia iimargin iiof iierror, iiwhich iiis iinormal) But iibias iiis iipresent iiwhen iithe iimargin iiof iierror iidiffers iisystematically iifrom iione iigroup iito iianother Whats iithe iidifference iibetween iibias iiand iimean iidifference? Mean iiDifference ii≠ iiBias Mean iidifference ii= iiWhen iitheres iia iitrue iidifference iithat iiexists iibetween iigroups ii - iiGroups iimay iitruly iidiffer iion iithe iiconstruct iieven iiif iithe iicause iiof iithe iidifference iiis iiunknown, iior iiwe iiideally iiwish iithe iidifferences iididn't iiexit Bias ii= iiWhen iithe iivalidity iiof iithe iitest iiis iidifferent iibetween iigroups - iiSomething iisystematically iiwrong iiwith iithe iitest iiso iione iigroup iialways iidoes iibetter iithan iithe iiother ii(which iidoes iinot iireflect iia iitrue iidifferent) The ii3 iiType iiof iiBias 1) iiContent iiValidity iiBias 2) iiConstruct iiValidity iiBias 3) iiPredictive iiValidity iiBias ii(criterion) Content iiValidity iiBias When iian iiitem iior iisub-scale iiis iisystematically iiMORE iidifficult iifor iimembers iiof iione iigroup iicompared iito iianother, iidespite iiskill iilevel iibeing iicontrolled iifor **Essentially iiitem iidifficulty!! (This iibias iiis iinot iiso iimuch iiabout iicontent ii-- iibut iirather iitest iidifficulty) How iito iiTest iifor iiContent iiValidity iiBias? 1) iiCreate iisubsamples iiwith iicomparable iiscores iion iithe iitest iiwithin iieach iicultural iigroup 2) iiWithin iithese iisubsamples, iiassess iithe iiitem iidifficulty iilevel iito iisee iiif iiit iidiffers iiacross iicultural iigroups ii(are iiscores iiconvertible iiacross iicultures?) - iiIf iiit iidiffer iifor iione iigroup, iithen iithose iiitems iimust iibe iireassessed iior iiremoved **Simply iiusing iiexpert iijudges iito ii"assess" iiwhether iithe iiitem iicontent iiis iiproper iidoes iiNOT iiwork, iibc iiexperts iiare iithemselves iimembers iiof iispecific iicultures! Construct iiValidity iiBias When iithe iitest iiassesses iidifferent iithings iiin iidifferent iigroups, iior iimeasures iiidentical iithings iiwith iidifferent iidegrees iiof iiprecision Predictive iiValidity iiBias Occurs iiwhen iithe iiquality iior iiprecision iiof iithe iiprediction ii(criterion -related) iisystematically iidiffers iiacross iigroups **Most iisneaky - iiVery iibad iiif iiused iiin iipractical iisettings iito iimake iidecision iiabout iiperson iibased iion iithese iipredictive iiresults ii(eg. iiselection) - iiLess iibad iiin iiresearch iisettings ii(not iieffecting iiimmediate iireal iiworld iiimplications iior iidecisions) The ii2 iiTypes iiof iiPredictive iiValidity iiBias: 1) iiSlope iiBias 2) iiIntercept iiBias Slope iiBias When iithe iicoefficient iiof iivalidity iiis iiNOT iithe iisame iiacross iigroups ii(aka iiwhen iislope iiof iiregression iiline iidiffers iiacross iigroups) ii **The iiWORST iiform iiof iibias ii(most iisevere) - iiVery iimessy iiand iidifficult iito iifix ii - iiPredictions iiare iiall iiover iithe iiplace ii(can't iiuse iitill iifixed) Visual: - iiThe ii2 iiregression iilines iiare iicrossed iiin ii(X) iishape, iirather iithan iibeing iithe iisame iiline - iiTest iiis iiNOT iipredicting iithe iisame iithing iiin iithe iisame iimanner iiacross iigroups ii(slope iifor iithe ii2 iilines iicompletely iidifferent) Intercept iiBias When iithe iisame iiscore iion iithe iitest iisystematically iipredicts iia iihigher iilevel iiof iiperformance iiin iione iigroup iithan iiother ii(aka iiwhen iiintercept iidiffers iiacross iigroups) **One iigroup iigets iia ii"bonus" iihead iistart iifor iino iireason ii(i.e. iiprecision iiproblem ) **Easy iito iiadjust iionce iiidentified - iiCan iistill iiuse iitest ii-- iijust iineed iito iibe iiaware iiand iiadjust iiprediction iiin iiaccordance iiwith iiintercept iidifference Visual: - iiThe iiregression iilines iiof iithe ii2 iigroups iiare iiparallel iito iione iianother Predictive iiValidity iiwith iiNo iiBias - iiTest iishows iimean iidifference - iiRegression iiequation iiis iithe iisame iifor iiboth iigroups ii(1 iiline iipassing iithrough iiboth iigroups) - iiPrediction iiof iithe iioutcome iiis iithe iisame iiacross iigroups Variable A iicharacteristic iion iiwhich iiindividuals iidiffer iifrom iione iianother Observed iivariable A iivariable iithat iican iibe iidirectly iiassessed/measured eg. iisex, iiage, iitenure, iiheight, iiweight, iietc. Latent iivariable A iivariable iithat iiCANNOT iibe iiobserved iiand iimeasured iidirectly **Can iionly iibe iimeasured iiindirectly eg. iiself-esteem Use iispecific iitests iiand iiquestionnaires iito iielicit iibehaviours iirelated iito iimeasure iithem How iito iiAssess iiPsychological/Latent iiConstructs By iisoliciting iia iirepresentative iisample iiof iithese iibehaviours iithat iiare iiboth iilimitative ii& iiinclusive Limitative ii= iilow iicost, iistrict iitime iiconstraint, iionly iirelevant iiinfo, iinot iitoo iimany iiquestions ii(fatigue) Inclusive ii= iicovers iiall iirelevant iiaspects ii(critical iicomponent) ***The iiquality iiof iithe iimeasurement ii(diagnostic iivalue) iiand iithe iiability iito iigeneralize iiits iiconclusions ii(predictive iivalue) iiis iiintimately iirelated iito iithe iidegree iito iiwhich iithis iisample iiof iibehaviors iiis iirepresentative iiof iithe iiconstruct Psychological iiConstruct ii(or iiLatent iiConstructs) An iiabstract iientity iithat iiwas iicreated iito iireflect iia iiset iiof iibehaviors iithat iitend iito iico-occur iiwith iione iianother