Intelligence & cognition

Fluid intelligence

LASA022 (B-G)
LASA222 (B-G)
LASA024 (B)

Contact: Hannie Comijs

Fluid intelligence is defined as the ability to deal with new information. Contrary to crystallized intelligence, fluid intelligence is particularly vulnerable to decline associated with aging (Horn, 1985; Smits, Smit, Van den Heuvel, & Jonker, 1997). Fluid intelligence is assessed with the Raven Coloured Progressive Matrices (RCPM, Raven, 1995). The RCPM is a non-verbal visual test, assessing the ability for non-verbal and abstract reasoning. The original version of the RCPM consists of three sections, A, Ab, and B. Each subset contains 12 items, and each item consists of a drawing (matrix) of a pattern from which a section is missing. On the bottom of the page six patterns are printed, one of which fits in the missing section. The respondent has to choose which of the six alternatives fits best. Each correctly chosen pattern counts for one point, resulting in a total scale score ranging from 0 to 24. The items increase in difficulty, and so do the three sections. Previous studies show a strong correlation between test performance and level of education (Smits et al, 1997), intellectual and visual spatial capacities (Raven, 1984), and dementia (Gainotti, Parlato, Monteleone & Carlomagno, 1992).

Measurement instrument in LASA
In LASA, only subset A and B is used due to time limitations. This adaptation does hardly effect the interpretation of the test performance as pilot studies showed a strong correlation (r = 0.96) between the sumscore of A, Ab and B and the sumscore of A and B (Deeg & Smit, 1993). If the response on one of the first three items of subset A is wrong, the interviewer gives feedback, until the object of the task is absolutely clear. At baseline (B) by means of three additional questions the respondents are asked to evaluate their performance on this test.

LASAB022 / LASAC022 / LASAD022 / LASAE022 / LAS2B022 / LASAF022 / LASAG022
(RAVEN ©, scoring protocol);
LASAB024 (main interview, in English  / in Dutch)

Variable information
The LASA022 files contain the scores on the individual items; the variable names for subset A are *RAVA1 for the first item to *RAVA12 for the last item; the variable names for subset B are *RAVB1 for the first item to *RAVB12 for the last item. The LASA222 files contain the sumscores. LASAB024 contains the scores on the evaluation of the Raven by the respondents (MECOG1, MECOG2, MECOG3).

LASAB022 / LASAC022 / LASAD022 / LASAE022 / LAS2B022 / LASAF022 / LASAG022;
LASAB222 / LASAC222 / LASAD222 / LASAE222 / LAS2B222 / LASAF222 / LASAG222 (sum scores)


The descriptive statistics of the Raven in all waves (B-G): (pdf).

Availability of information per wave1: 


























Ma - - - - - - - - - -

1 More information is available on:

* 2B=baseline second cohort;
   3B=baseline third cohort;
   MB=migrants: baseline first cohort (Under Construction);
I=Under Construction

Ma=data collected in main interview;
Me=data collected in medical interview

Previous use in LASA
RCPM is often used as one of the indicators of verbal or fluid intelligence in studies on cognitive ageing (Aartsen et al., 2004; Zimprich et al., 2004), or as predictor of change in other domains of functioning (Aartsen et al, 2002; Van Schoor et al., 2002), or as a dependent variable (Aartsen et al., 1998; Aartsen et al., 2002; Dik et al., 2003), or as a factor that was associated to other domains of functioning (Comijs et al., 2001).


  1. Aartsen, M.J., Martin, M, & Zimprich, D (2004). Gender differences in level and change in cognitive functioning: Results from the Longitudinal Aging Study Amsterdam. Geronto logy, 50, 35-38.
  2. Aartsen, M.J., Smits, C.H.M., Van Tilburg, T.G., Knipscheer C.P.M. & Deeg, D.J.H. (2002). Activity in older adults: Cause or consequence of cognitive functioning? A longitudinal study on everyday activities and cognitive performance in older adults. Journal of Gerontology, 2, 153-162.
  3. Aartsen, M.J., & Smits, C.H.M. (1998). Age, gender, level of education and functional limitation as determinants of change in cognitive functions. In D.J.H. Deeg, A.F.T. Beekman, D.M.W. Kriegsman, & M. Westendorp -de Seriere (Eds.), Autonomy and well-being in the aging population II. Report from the Longitudinal Aging Study Amsterdam 1992-1996 . (pp. 71-82). Amsterdam: VU-University Press.
  4. Comijs, H.C, Jonker, C., Beekman, A.T.F. & Deeg, D.J.H. (2001) The association between depressive symptoms and cognitive decline in community-dwelling elderly persons. International Journal of Geriatric Psychiatry, 16: 361-367.
  5. Dik, M.G., Pluijm, S.M., Jonker, C., Deeg, D.J., Lomecky, M.Z. & Lips, P. (2003). Insulin-like growth factor I (IGF-I) and cognitive decline in older persons. Neurobiological Aging 24(4):573-81.
  6. Gainotti, G., Parlato, V., Monteleone, D. & Carlomagno, S. (1992). Neuropsychological markers of dementia on visual-spatial tasks: A comparison between Alzheimer's type and vascular forms of dementia. Journal of Clinical and Experimental Neuropsychology , 14: 239-252.
  7. Raven J.C. (1995). Manual for the Coloured Progressive Matrices (revised) . Windsor, UK: NFRE-Nelson.
  8. Smits C.H.M, Smit J.H., Van den Heuvel, N. & Jonker, C. (1997). Norms for an abbreviated Raven's Coloured Progressive Matrices in an older sample. Journal of Clinical Psychology , 53(7): 687 -697.
  9. Van Schoor N.M., Smit, J.H., Pluijm, S.M, Jonker, C., & Lips, P. (2002). Different cognitive functions in relation to falls among older persons. Immediate memory as an independent risk factor for falls. Journal of Clinical Epidemiology, 55(9):855-62.
  10. Zimprich, D., Hofer, S., & Aartsen, M.J. (2004). Short-term versus long-term changes in processing speed. Gerontology, 50, 17-21.