3. IQ data set

3.a) Available statistical IQ data set

3.a.1 Young Adulthood Study

The current statistical research has been performed with the IQ data set contained in the Young Adulthood Study: 1939-1967 [made accessible in 1979 on electronic files]. This IQ data set was collected by Virginia Crandall and made available through an archive at the Henry A. Murray Research Center of The Radcliffe Institute for Advanced Study, Harvard University, Cambridge, Massachusetts [Producer and Distributor]

This collection of longitudinal data contains the variables we are interested in: those relative to the intelligence quotients (IQ) of parents and their corresponding children. The statistical data reliability is assued.

After a preliminary analysis of the available statistical IQ data set, one variable for the mothers (M) (Otis intelligence test), fathers (F) (Otis test) and children (C4) was used with 70 corresponding values, two more from the children (C1 and C5) with 69 corresponding values, and another set of three variables of the children with less corresponding values (C2, C3, and C6 with values of 58, 42, and 64 respectively) that we will use only to create variable X6, the average of the children's six variables.

The statistical IQ data set is taken from average class white families, with a mean IQ of 110, slightly above the average. For each family, the data source corresponds to the father, the mother, and one child.

 
YOUNG ADULTHOOD STUDY
(Statistical IQ data set)
Variables Name Reference Period and Statistical data set
Mothers M 186 d12c66 T3 mothers IQ data (otis)
Fathers F 187 d12c70 T3 fathers IQ data (otis)
Children C1/T1 201 d13cl62 T1 Stanford-Binet IQ data, score at ages 3, 6, 10-old/10
C2 217 d14cl62 T2 Stanford-Binet IQ data, score at ages 3, 6, 10-old/10
C3 233 d15cl62 T3 Stanford-Binet IQ data, score at ages 3, 6, 10-old/10
C4/T4 185 d12c62 T4 IQ data at age 12
C5/WB 273 d18c30 T4 Wechsler-Bellevue IQ data, @ 13 yrs, perf
C6 318 d20c62 Primary Mental Abilities-ttl (17-18 yrs.)
C7 279 d18c54 T4 Wechsler-Bellevue IQ data, recent perf
  X3     = (C1+C4+C5) / 3
  X6     = (C1+C2+C3+ C4+C5+C6) / 6
  T1-d     = C1 smoothed tails, 10% of X6

3.a.2. Limitations of statistical data set

  • Sample size of statistical IQ data set

    This is a limitation that could become very serious, although the sample size is 70 (n=70) (Otis IQ test of mothers and fathers and one of the children), when we make the analysis by groups it is reduced to only 7 groups with a sample size of 10 in each one.

    Logic and correlation
    Logic and correlation

    Nevertheless, we do the mentioned grouping for values of 2, 3, 4, 5, 6, 7, 8, 9 and 10. In addition, different groupings are created depending on the order the 70 values can be rearranged.

    In this way, as you will see in the following sections, we multiplied the number of studied variables by more than 50. Consequently, the model becomes very sensitive to small statistical data set modifications in the different groupings.

    The different variables suppose different views on the same statistical data set; in other words, they will simultaneously provide estimations of the existing correlations in different dimensions.

    In my opinion, this sensitivity is the strongest point of the model: the good adjustments obtained are very significant regarding the goodness-of-fit of this model's structure, especially because they have been obtained without any modification of the original variables allowing a total statistical data reliability.

    The strength of the analysis performed allowed the initial objectives to be achieved and much more.

  • Statistical IQ Data set quality

    As shown in the previous table of the statistical data set and selected variables, it should be emphasized that the test types or methods of evaluation used were not the same.

    Likewise, the existence of values considered extreme should be taken out when they are not reasonable.

    There is only one statistical data set for the parents' IQ whereas for the children there are various IQ data set that, as we will see, are not highly correlated at all.

    Even so, these limitations should reinforce the obtained results since, with a more precise global statistical data set, it would be expected that there would be a higher correlation between variables.

    Anyway, the fact that this is a relatively homogenous sample will also work against the study's objective, because it will be more difficult to discriminate between the study's values. Therefore, the results would be more relevant.

  • Temporary stability of intellectual ability

    The different IQ data set of children has been obtained for along different years. Without having reached a clear conclusion, it is fair to say that the temporary stability of the statistical IQ data set is compatible with the different observed values in the model's simulation.