Resmrch Note

Prediction Studv of Rdult Creative Rchievement: Torrance’s longitudinal StudV of CreotivitV Revisited

H l R O V U K l Y A M A D A A L I C E Y U - W E N TAM

ABSTRACT The purpose of this study is to reanalyze Torrance’s longitudi- nal study (1981) by employing a multiple regression analysis to find the best predictors for adult creative achievement. A total of 211 cqses were available for this study. The results of the regression analysis led to the predictive rule that com- prised the following predictors: creativity test score, childhood future career image, intelligence test score, and the existence of a mentor. These four predictors explained 49% of the total variance in adult creative achievement.

INTRODUCTION Torrance’s longitudinal study, which began in 1958, focused on the prediction of adult creative achievement. However,. intercorrelations a m o n g predictor variables were no t considered in the earlier study (Torrance, 1981). This could lead to a false conclusion concerning the relative contribution of predictors to creative achievement. The purpose of this study is to reanalyze Torrance’s longitudinal study data employing a multiple regression analysis to predict adult creative achievement.

METHOD Data on a total of 211 subjects, 95 males and 116 females, were available for this study. These were the same as the original data used in the correlation anafyses (Torrance, 1981).

Four criterion variables.were obtained as indicators of adult creative achievement (Torrance, 1981 ): (a) number of post- high school creative achievements, (b) number of creative style of life achievements, (c) quality of highest creative achievements, and (d) creativeness of future career image. The four criterion variables, each of which was standardized

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Journal of Creative Behavior

to a z-score to equalize otherwise widely divergent variances, were empfoyed to form a single composite score for adult creative achievement (the Cronbach coefficient alpha of this score was .85). Taking the results of Torrance (1981) into consideration, the following variables were chosen a s the initial predictors: creativity index (CI), childhood future career image (CFCI), foreign experience (FWP), Buck's HouseTree Person Test (HTP), intelligence test (IQ), time out (TO), and mentor (MENTOR).

TABlE 1 . Correlation Matrix Among Variables

Variable 1 2 3 4 5 6 7 8

1. ACA -

2. CI

3. CFCl

4. F U P

5. HTP

6. IQ

7. TO

8. MENTOR

.61 .43 .22 .20 .29 -15 .30 (211) (206) (211) (181) (156) (211) (211) - .45 .25 .22 .24 .15 .20

.(206) (211) (181) (156) (211) (211) - .28 .12 .11 .08 .22

(206) (178) (152) (206) (206)

(181) (156) (211) (211)

- .04 .09 .I9 (150) (181) (181)

- .12 .09 (156) (156) - -07

- .13 .19 .29 .15

(211)

Note. The values in parentheses reflect the sample size for each pair. ACA = adult creative achievement; CI = creativity index; CFCl = childhood future career image; FEXP = foreign experience; HTP = Buck's House-Tree-Person Test; I Q = intelligence test; TO = time-out experience; MENTOR = having had a mentor.

RESULTS The correlation matrix for the variables employed in this study was reported in Table 1. HTP was deleted from further analy- sis due to its lack of correlation with IQ, which was estimated to be a more valid and reliable measure of intelligence. Based on the intercorrelation coefficients, no serious multicollinearity

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Prcdictlon Study of Adult Creative Achievement: Torrance's Longltudinal Study of Creativity Revisited

problem appeared to be present. The examination of the data conditions revealed that the normality assumption for the residuals was slightly violated (e = .048), and that the variance did not appear constant. Because of these condi- tions, a square root transformation was used (Montgomery & Peck, 1992). Further inspection of the data indicated that two cases were outliers and influential data points. Because no coding errors were detected, these two cases were regarded a s special cases and were removed. The resulting distribution of the error term was normal (Q = .105) and the variance appeared constant. To determine the best subset size of pre- dictors, the all possible regression approach was performed using PROC REG/SELECTION=ADJRSQ MSE CP in SAS Version 6.08 (SAS, 1990). Based on the adjusted R2 (R2n), MSE, Cp, and the parsimony principle, the best subset size was determined to be four. Further examination of the results found no evidence of violation of normality (Q = .106), homoscedasticity of the residuals, multicollinearity, or serious influential data points and outliers.

TFIBLE Q. Regression Analysis With Four Predictors

Variable - b - b' _t €2

CI .03 .44 6.30 .0001 CFCl .64 .24 3.47 .0003 I Q .02 .20 3.30 .0012 MENTOR .57 .16 2.60 .0104

Note. CI = creativity index; CFCl = childhood fqture career image; IQ = intelligence test; MENTOR = having had a mentor. - b = unstandardized regression coefficients; - b' = standardized coefficients.

The four variables composing the best subset were CI, CFCI, IQ, and MENTOR. The composite of these four variables explained 49% (Bzn=.48.97) of the total variance of adult cre- atiye achievement. In addition, there was an overall significant linear relationship between the criterion variable and the pre- dictor variables [(F(4,145) = 36.75, ~<.0001]. Table 2 showed that the regression coefficients of the four predictors were statistically significant at the .0125 level using the Bonferroni correction method. Further, the relative contribution of the

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Journal of Creative Behavior

predictors to the prediction of adult creative achievement was examined based on t-values for the regression coefficients. The creativity index seemed to be the best predictor, child- hood future career image and IQ the second, followed by having had a mentor the third.

DISCUSSION Results of this study reaffirm the importance of the creativity index measured by the Torrance Tests of Creative Thinking (lTCT) as the best predictor for adult creative achievement. The stability of childhood future career image also appeared to be conducive to higher adult creative achievement. In addi- tion to these two predictors, having had a mentor is an important factor of adult creative achievement. However, this predictor might not be as crucial as the two predictors above. One possible reason is that it was measured dichotomously, i.e., whether the person had a mentor or not; hence, the amount of variability is limited. Questions that would yield continuous data such as the period for which the person had a mentor and the number 6f mentors might allow this predictor to con- tribute more to the prediction of adult creative achievement.

On the other hand, the results of this study reveal that IQ has a s much a predictive power for adult creative achieve- ment as the childhood future career image. This finding seems to be contradictory to those reported by Torrance (1981, 1987; Torrance G Wu, 1981). However, Simonton (1991) suggested that intelligence “may form part of a generic personality p r e file that contributes to the achieved eminence of both creators and leaders” (p. 76). Further, some researchers (Wallach & Kogan, 1976) believe that intelligence as well a s creative think- ing abilities, which are not highly correlated with each other in the context of measurement, might be necessary to acquire creative achieyements, although the former does not contrib- Ute to the prediction of adult c{eptive achievement so much as the latter. The finding from this study may suggest that the phenomenon of creative productivity involves irhelligence.

Overall, this study would strongly support Torrance’s ear- lier results concerning the prediction of adult creative achievement. The difference between the earlier results and the present ones lies in the intelligence’s role in the predic- tion. Contrary to the earlier results (Torrance, 1981), this study may suggest that higher intelligence is necessary for publicly recognized creative achievements. Furthermore, to construct a more accurate predictive model, more information on per- sonality traits such as aggressiveness (Simonton, 1991) and

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Prcdiclion Study of Adult Creative Achievement: Tomnce’s Longitudinal Study of Creativity Revlsltcd

environmental factors such a s socioeconomic status (Walberg, 1988) should be included. Also, the question regarding a mentor should be redefined in order to provide larger amount of information that might enhance its predictive power.

One limitation of this study is the correlational nature of the analysis. A frequently made misinterpretion of correlational results is causation. Although the four variables were found to be piedictive of adult creative achievement, they by no means “cause” creative behaviors. The statistical procedure applied in the present study offers a parsimonious list of variables that should be interpreted a s follows: if an individual scores high on a creativity test, has clear career image a s a child, scores above average on an intelligence test, and has a mentor in life, he/she is likely to exhibit creative behaviors a s an adult. As noted in the previous paragraph, additional personal arid environmental characteristics should be exam- ined in order to provide a better understanding of human creative behaviors.

Presently, elementary school children who participated in Torrance’s longitudinal study are of middle age. This age corresponds to Erikson’s (1964) development: stage of generativity vs. stagnation. It would be intriguing to investi- gate what they have achieved creatively at this point in their lives, especially in terms of “‘real-life’ creative behavior” (Torrance, 1988, p. 62).

A G E A E N C E S ERIKSON, E. H. (1964). Childhood and society (2nd ed.). New York’:

MONTGOMERY, D. C., G PECK, E. A. (1992). lntroduclion to linear

SAS INSTITUTE INC. (1990). SAS/STAT user’s guide, Version 6 (4th ed.). Cary, NC: Author.

SIMONTON, D. K. ( 1991). Personality correlates of exceptional personal influence: A note on Thorndike’s ( 1950) creators and leaders. Creativity Research Journal, 4,67-78.

TORRANCE, E. P. (1981). Predicting the credtivity of elementary school children (19581980) - and the teacher who “made a difference.” Giiled Child Quarterly, 25,55-62.

TORRANCE, E. P. (1987). Future career image a s a predictor of creative achievement in a 22-year longitudinal. study. Psychological Reports, 60,574.

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regression analysis (2nd ed.). New York: Wiley.

TORRANCE, E. P. (1988). The nature of creativity as manifest in its testing. In R. J. Sternberg (Ed.), The nature ofcreatiuity (pp. 43-75). New York: Cambridge University Press.

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TORRANCE, E. P.. G WU, T. (1981). A comparative longitudinal study of the adult creative achievements of elementary school children identified a s highly intelligent and a s highly creative. Creative Child and Adult Quarterly, 6. 71-76.'

WALBERG, H. J. (1988). Creativity and talent a5 learning. In R. J. Sternberg (Ed.), The nature of creativity (pp. 340-361). New York: Cambridge University Press.

WALLACH. M. A.. & KOGAN. N. (1976). Creativity and intelligence in children. In A. Hothenberg & C. R. Hausman (Eds.). The crealiuily quesfion (pp. 208217). Durham, NC: Duke University Press. (Original work published 1972).

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Hiroyuki Yamada, EP Division, School of Education, University of California, Berkeley, California 94720. Electronic mail may be sent vla internet to hryamada@violet. berkeley.edu. Alice Yu-Wen Tam, Department of Educational Psychology, University of Georgia, Athens, GA 30602.

Author Note

We gratefully acknowledge Dr. E. Paul Torrance who kindly offered us his longitudinal data. We would also like to thank Dr. Bonnie Cramond for her helpful comments on our earlier manuscript .

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