Personality and Transformational and Transactional Leadership: A Meta-Analysis

1. By Joyce E. Bono & Timothy A. Judge Personality and Transformational and Transactional Leadership: A Meta-Analysis Presented by ArasSoxxx and TomekKosalka

2. Meta-Analysis “Meta-analysis refers to the statistical analysis of a large collection of results from individual studies for the purpose of integrating the findings. “ (Glass, 1976)

3. Glossary • Fixed effect : Statistic is true value (assumed) • Random effect: Expected statistic is true value Choice is likely to affect the effect size estimation • Confidence Interval (CI) : The range of values which includes the mean of the true value • Credibility Interval (CR) : The range of values which is expected to include a percentage of the random variable

4. Meta-Analysis • Effect sizes for each study • Need for common metric • Correct and weight the effect sizes • Eliminate bias (measurement error, sample size etc.) • Obtain the mean effect size across studies • Fixed Effect vs. Random Effect vs. Mixed Effect • Convert to a Z-score • Confidence Interval (CI)

5. How to Conduct a Meta-Analysis? • Report Results • Number of primary studies (k) • Total sample sizes (N) • Observed distribution of effect sizes: and SDr (that is, the distribution before any corrections are made) • Real distribution of true effect sizes: and SDρ • Confidence Interval (95%CI) of the true effect sizes: Showing the extent to which the mean true effect size varies due to sampling error. • Credibility Interval (80%CrI – 10%CV and 90%CV): Showing the real variation of true effect sizes (Credibility Interval is calculated based on SDρ ) • Percent of variance accounted for by artifacts: Percent of the observed variation in the effect sizes can be explained by artifacts (Rule of thumb: if this value is ≥ 70%, there’s unlikely to be any meaningful moderators).

6. How to Conduct a Meta-Analysis? √ √ • Report Results • Number of primary studies (k) • Total sample sizes (N) • Observed distribution of effect sizes: and SDr (that is, the distribution before any corrections are made) • Real distribution of true effect sizes: and SDρ • Confidence Interval (95%CI) of the true effect sizes: Showing the extent to which the mean true effect size varies due to sampling error. • Credibility Interval (80%CrI – 10%CV and 90%CV): Showing the real variation of true effect sizes (Credibility Interval is calculated based on SDρ ) • Percent of variance accounted for by artifacts: Percent of the observed variation in the effect sizes can be explained by artifacts (Rule of thumb: if this value is ≥ 70%, there’s unlikely to be any meaningful moderators).

7. Hunter – Schmidt Method I (Bare-bones): Observed distribution of effect sizes Mean Effect Size Confidence Interval r: correlation coefficient k studies, Ni observations

8. How to Conduct a Meta-Analysis? √ √ • Report Results • Number of primary studies (k) • Total sample sizes (N) • Observed distribution of effect sizes: and SDr (that is, the distribution before any corrections are made) • Real distribution of true effect sizes: and SDρ • Confidence Interval (95%CI) of the true effect sizes: Showing the extent to which the mean true effect size varies due to sampling error. • Credibility Interval (80%CrI – 10%CV and 90%CV): Showing the real variation of true effect sizes (Credibility Interval is calculated based on SDρ ) • Percent of variance accounted for by artifacts: Percent of the observed variation in the effect sizes can be explained by artifacts (Rule of thumb: if this value is ≥ 70%, there’s unlikely to be any meaningful moderators). √ √

9. Hunter – Schmidt Method I (Bare-bones): Real distribution of effect sizes Estimated variances for a meta-analysis: for r: for a study: for rho:

10. How to Conduct a Meta-Analysis? √ √ • Report Results • Number of primary studies (k) • Total sample sizes (N) • Observed distribution of effect sizes: and SDr (that is, the distribution before any corrections are made) • Real distribution of true effect sizes: and SDρ • Confidence Interval (95%CI) of the true effect sizes: Showing the extent to which the mean true effect size varies due to sampling error. • Credibility Interval (80%CrI – 10%CV and 90%CV): Showing the real variation of true effect sizes (Credibility Interval is calculated based on SDρ ) • Percent of variance accounted for by artifacts: Percent of the observed variation in the effect sizes can be explained by artifacts (Rule of thumb: if this value is ≥ 70%, there’s unlikely to be any meaningful moderators). √ √ √

11. Hunter – Schmidt Method I (Bare-bones): Credibility Interval range of values which is expected to include a percentage of the variation of a random variable

12. How to Conduct a Meta-Analysis? √ √ • Report Results • Number of primary studies (k) • Total sample sizes (N) • Observed distribution of effect sizes: and SDr (that is, the distribution before any corrections are made) • Real distribution of true effect sizes: and SDρ • Confidence Interval (95%CI) of the true effect sizes: Showing the extent to which the mean true effect size varies due to sampling error. • Credibility Interval (80%CrI – 10%CV and 90%CV): Showing the real variation of true effect sizes (Credibility Interval is calculated based on SDρ ) • Percent of variance accounted for by artifacts: Percent of the observed variation in the effect sizes can be explained by artifacts (Rule of thumb: if this value is ≥ 70%, there’s unlikely to be any meaningful moderators). √ √ √ √

13. Problems (Artifacts) • Sampling error • Measurement error • Reliabilities • Range restriction • Dichotomization N = 80 , d = .40 Type I = 5% Type II = 50% (Hunter & Schmidt,1990)

14. Hunter Schmidt Method II (Psychometric Meta-Analysis): CORRECTIONS 1- Reliability Artifacts:

15. Hunter Schmidt Method II (Psychometric Meta-Analysis): CORRECTIONS 2- Range Restriction Artifacts: Direct Restriction Indirect Restriction : Reliability of IV in unrestricted data

16. Hunter Schmidt Method II (Psychometric Meta-Analysis): • Which correction first? Order depends! First, correlations for each study… • If DIRECT RANGE RESTRICTION • First then range rest., then • If INDIRECT RANGE RESTRICTION: • First reliability ( ) then range restriction CORRECTIONS

17. Hunter Schmidt Method II (Psychometric Meta-Analysis): • Which correction first? Order depends! Second, we need the compound attenuation factor (A) and sampling variance for each study… Sampling variance for disattenuated r CORRECTIONS

18. Hunter Schmidt Method II (Psychometric Meta-Analysis): • Which correction first? Order depends! Second, we need the compound attenuation factor (A) and sampling variance for each study… Range restriction? Adjust for it. : adjustment for range restriction CORRECTIONS

19. Hunter Schmidt Method II (Psychometric Meta-Analysis): WEIGHTED MEAN AND VARIANCE

20. Hunter Schmidt Method II (Psychometric Meta-Analysis): AVERAGE CORRECTED r SAMPLING ERROR CORRECTED VARIANCE OF RHO

21. How to Conduct a Meta-Analysis? √ √ • Report Results • Number of primary studies (k) • Total sample sizes (N) • Observed distribution of effect sizes: and SDr (that is, the distribution before any corrections are made) • Real distribution of true effect sizes: and SDρ • Confidence Interval (95%CI) of the true effect sizes: Showing the extent to which the mean true effect size varies due to sampling error. • Credibility Interval (80%CrI – 10%CV and 90%CV): Showing the real variation of true effect sizes (Credibility Interval is calculated based on SDρ ) • Percent of variance accounted for by artifacts: Percent of the observed variation in the effect sizes can be explained by artifacts (Rule of thumb: if this value is ≥ 70%, there’s unlikely to be any meaningful moderators). √ √ √ √ √

22. The study itself

23. Purpose of the Study • Extend what is known about the association between personality and leadership by focusing directly on the relationship between personality and the eight dimensions of transformational and transactional leadership. • These dimensions have been found to be valid predictors of follower job performance and satisfaction.

24. Transformational Leadership • Idealized influence: leaders who have high standards of moral and ethical conduct, and who engender loyalty from followers. • Inspirational motivation: leader with a strong vision for the future based on values and ideals. Stimulates enthusiasm, builds confidence, & inspires through symbolic action and persuasive language. (1 & 2 combined=charisma) • Intellectual stimulation: leaders who challenge org. norms, encourage divergent thinking, and who push followers to develop innovative strategies. • Individual consideration: leader behaviors aimed at recognizing the unique growth/development needs of followers.

25. Transactional Leadership 5. Contingent reward: leaders behaviors focused on exchange of resources. Provide tangible and intangible support and resources to followers in exchange for efforts & performance • Management by exception-active: monitoring performance and taking corrective action as necessary (i.e., sets standards and monitors deviations) • Management by exception-passive: leaders take a passive approach, intervening only when problems become serious. • Laissez-faire: thought of as nonleadership or the avoidance of leadership responsibilities.

26. Dimensions of Leadership • At least in some extant, survey measures of TFL and TAL confound perceptions, attributions, and implicit theories with behaviors. • Association between personality and six dimensions of leadership (charisma, intellectual stimulation, individualized consideration, CR, MBEA, and MBEP-LF) were examined.

27. Extraversion • Described as assertive, talkative, upbeat, energetic and optimistic. • They seek excitement and social attention • Experience and express positive emotions • Generate confidence and enthusiasm in followers because they are positive, ambitious and influential • Score high on intellectual stimulation because they tend to seek out and enjoy change

28. Neuroticism • Tendency to experience negative affects, such as fear, sadness, guilt, and anger. • High score indicates emotional distress while a low score reflects calm, even tempered and relaxed. • These people are not seen as role models and unlikely to have a positive view of the future. As such, it is unlikely that they will exhibit TFL behaviors such as idealized influence, inspirational motivation and intellectual stimulation.

29. Openness to experience • Tendency to be creative, introspective, imaginative, resourceful, & insightful • High score indicates they are emotionally responsive, intellectually curious, have flexible attitudes and engage in divergent thinking • Associated with TFL, specifically intellectual stimulation and inspirational motivation

30. Agreeableness • Tendency to be cooperative, trusting, gentle and kind • They value affiliation and avoid conflict because they are modest, altruistic, and usually trusting and trustworthy • High scores associated with individual consideration, contingent reward, idealized influence • Low scores on passive leadership

31. Conscientiousness • Usually have a strong sense of direction, work hard to achieve goals, cautious, deliberate, self-disciplined, and are neat and organized. • Associated with contingent reward and management by exception-active • Unlikely to exhibit passive leadership behaviors

32. Hypotheses • Hypothesis 1: Extraversion will be positively related to (a) charisma, (b) intellectual stimulation, and (c) and TFL overall • Hypothesis 2: Neuroticism will be negatively related to (a) charisma, (b) intellectual stimulation, and (c) TFL overall, and positively related to (d) passive leadership

33. Hypotheses (continued) • Hypothesis 3: Openness to experience will be positively related to (a) charisma, (b) intellectual stimulation, and (c) TFL overall • Hypothesis 4: Agreeableness will be positively related to (a) charisma, (b) individualized consideration, and (c) contingent reward, and negatively related to (d) passive leadership

34. Hypotheses (continued) • Hypothesis 5: Conscientiousness will be positively related to (a) contingent reward, (b) management by exception-active, and negatively related to (c) passive leadership

35. Method • Search for studies between 1887 and 2002 yielded 26 articles containing 384 correlations • Hunter & Schmidt (1990) method • Calculated a sample-sized weighted mean correlation for each of the traits with each leadership dimension and corrected the correlations • Credibility intervals at 80% and 95% confidence intervals

36. Results: TFL

37. Results: TFL

38. Results: TFL

39. Results: TFL

40. Results: TAL

41. Results:TAL

42. Results: TAL

43. Results: Dimensions & Personality

44. Discussion: • Overall, the results linking personality with ratings of transformational and transactional leadership behaviors were weak (Variance explained was only as large as12%) • Why?

45. Discussion: • (A) Perhaps TFL & TAL are not as heritable or trait-like as are leadership emergence and effectiveness • (B) TFL & TAL may have dispositional antecedents that cannot be captured in 5 factor analysis • (C) Used ratings of leadership at work which may have reduced the personality-leadership link

46. Discussion: • TFL and TAL behaviors are more malleable, more transient, and less trait-like than one might otherwise believe. • Evidence suggests that TFL behavior can be learned and that life experiences play a role in the development of TFL

47. Discussion: • Possibility that specific trait-leadership links are obscured by lumping narrower traits into the 5 factor model • Post hoc analysis was done linking TFL composite to the Big 5 using only studies that explicitly measured Big 5

48. Discussion: Does not address whether the Big 5 are the most theoretically relevant traits for studying the dispositional bases of TFL and TAL. Continued use of the Big 5 may not be fruitful

49. Discussion: • The personality basis for TFL-TAL is weaker than that of leadership effectiveness and emergence. • It may be that the strong situations characteristic of org. settings suppress, to some degree, the natural demonstration of TFL-TAL

50. Questions: • All of the significant true correlations are slightly larger than the observed correlations. Is it possible that there is amoderator creating this difference (in addition to range restriction andreliability) or is the difference too small? • How large does the gap between the true correlation and the observed correlation need to be to indicate the potential for a moderator effecting the relationship?