Presentation on theme: "Department Psychology Matthias Ziegler People fake! - So what?"— Presentation transcript:
Department Psychology Matthias Ziegler People fake! - So what?
Matthias Ziegler2 Contents The BIG 5 – Knowldege and questions? Study design 3 questions General Conclusion
Matthias Ziegler3 The BIG 5 – Knowldege and questions? Latent State Trait Theory (LST) Steyer, Ferring & Schmitt (1992) - up to 20% of variance in a questionnaire state or interaction (Deinzer et al. 1995) Correlations between personality dimensions increase due to faking - Schmit & Ryan, 1993; Pauls & Crost, 2005 Meta-analytical evidence for correlated dimensions -Mount, Barrick, Scullen & Rounds (2005) -true correlations up to ρ =.52 between N and C - Higher order personality factors ( α & β, Digman, 1997) There is a situational influence when measuring personality How does that influence impact construct validity?
Matthias Ziegler4 The BIG 5 – Knowldege and questions? BIG 5 prediciting job performance -C r =.31 Meta analysis Barrick, Mount & Judge (2001) BIG 5 prediciting academic performance -Furnham & Chamorro Premuzic 12 % incremental validity to IQ BIG 5 predict performance Where does the predictive power come from? Trait or fake?
Matthias Ziegler5 The BIG 5 – Knowldege and questions? What happens when people fake? -Models for faking from McFraland and Ryan (2001), Snell et al. (1999) little empirical support/research -new model from Mueller-Hanson, Heggestad & Thornton (2006) published after my project faking regarded equal between people (but Zickar, Gibby & Robie, 2004) Study idea -qualitative analysis using cognitive interviews -Mixed Rasch Model (C) to detect different answer styles -explore differences between the classes
Matthias Ziegler6 Study design Integration of LST Theory and ICE Design (Steyer, 2005) -2 measurement times (LST) NEO – PI – R twice variance can be split into faking and personality -2 groups (ICE) CG normal instructions twice EG 2 nd time concrete situation (test for student selection, good result, expert) causal interpretation possible Hypotheses -H 1 : A specific faking takes place in the EG correlations between faked dimensions increase -H 2 : Controlling situational demand strongly diminishes correlations
Matthias Ziegler7 C11 e C12 e C21 e C22 e C31 e C32 e C41 e C42 e C51 e C52 e C61 e C62 e State 1 State 2 (Fake) State 1: CG = EG + CG: State 1 = State 2 State 2: EG > CG LST Theory + ICE Design C
Matthias Ziegler8 Results 1st semester psychology students -N CG = 94 N EG = 92, about 70% females in both groups -demografics comparable What was faked? CGEG N-0.14*-2.36*** E-0.050.90*** O-0.080.23 A0.121.05*** C-0.10*2.23*** Cohen‘s d for repeated measurement designs Except for O all means differ substantially (and significantly) from time 1 to time 2 in the EG but not in the CG.
Matthias Ziegler9 Results What happened to the correlations? Time 1 Time 2 Above the diagonal are the correlations within the control group and beneath the diagonal within the faking group. * p <.05 ** p <.01 Correlations increase despite diminished variance! NEAC N-.40**.08-.26** E-.40**-.05.11 A-.33**.14.04 C-.20.10.15 NEAC N-.42**.13-.28** E-.42**-.06.11 A-.39**.32**.03 C-.78**.46**.34**
Matthias Ziegler10 Results fit indices of SEM -χ ² = 3768.03 (2051), Bollen Stine p =.33 -CFI =.81; RMSEA =.067 (.064 -.071); SRMR =.138 means and latent means between groups Groups differ significantly only in their amount of faking after controlling for situational demand! d w/o sit d sit N-1.31***.42 E.99***.01 A.60***.25 C1.44***.71 state1-set equal state2-5.97***
Matthias Ziegler11 Results What happened to the correlations? -Not part of the model not necessary; inclusion does not improve model (neither does a higher order factor!) Correlations diminish drastically (E and A!) significant state and trait variance (E!) mostly substantial trait and state paths NEAC N-.02-.43**-.09 E-.42**.76**.05 A-.39**.32**.12 C-.78**.46**.34**
Matthias Ziegler12 Conclusion I faking had a causal effect on structure and means of the BIG 5 -specific faking took place causing highly inflated correlations (H 1 ) and mean differences (except for Openness) controlling the situational demand (H 2 ) -both groups have the same means in personality dimensions -correlations diminished uncorrelated BIG 5 structure in both groups Extraversion and Agreeableness still share a lot of variance explains troublesome SRMR replication in larger and different (applicant) samples
Matthias Ziegler13 Next question What predicts performance? -trait or state (faking)
Matthias Ziegler14 Very complex design only faked facors were used -Pauls & Crost (2005) within the CG loadings on the dimensions were set equal for each dimension -Allik & McCrae (2004) Model fit χ² = 3977.98 (2175), Bollen Stine p =.38 CFI =.80; RMSEA =.067 (.064 -.070); SRMR =.137
Matthias Ziegler15 Results What predicts performance? Dimension variance drops loadings only from 1 or 2 facets EG t1t2SEM N -.20-.16-.15 E -.16-.13-.15 A -.22*.04-.26* C.14.03.09 state 2 - -.09 R².09.03.13
Matthias Ziegler16 Results What is faking? -correlations between faking variance and other measures CGEG gf.07-.08 gc.02.13 SOE-.02-.08 SEB.07.31**
Matthias Ziegler17 Conclusion II criterion validity as effect size remains stable faking variance adds only little to the prediction -but positively faking does influence construct validity - only few facets predict performance faking is related with self efficacy beliefs Question What happens when people fake?
Matthias Ziegler18 Question 3 – What happens when people fake? Qualitative analysis -N = 50 -2 different faking strategies were used slight faking and extreme faking -only relevant items were faked -unimportant items were answered honestly or neutrally Mixed Rasch Model -3 class solution had best fit regular respondents (4%), slight faker (69%), and extreme faker (27%)
Matthias Ziegler19 Differences between the classes multinomial logistic regression with rr as reference categoy no differences in criterion validity (R² =.02) χ²B (sf)B (ef)Wald χ2 (sf)Wald χ2 (ef) A10.15*-.005.037*.174.97 C26.07***.054***.047*21.1210.10 gf1.67-.004.014*.12.68 gc.63-.228-.240.58.37 SOE1.81-.030-.152.111.55 SEB12.04*-.081.0912.691.98 age5.89-.066-.1333.793.29 gender188.8.131.526.252.09
Matthias Ziegler20 Conclusion III only important items are faked 2 different faking styles faking depends on trait, ability, age, and gender no differences in criterion validity
Matthias Ziegler21 General Conclusion Model of Responding to Situational Demand
Matthias Ziegler22 Contact Matthias Ziegler Ludwig-Maximilians-University Munich Department Psychology Leopoldstraße 13 80802 München phone: +49 89 / 2180 6066 fax: +49 89 / 2180 3000 Email: firstname.lastname@example.org Thank you for your attention!