Spatial Insight Test - Statistics

Remark

This test can no longer be taken, and most of its items are now included in The Marathon Test (in revised form where needed).

Scores on Spatial Insight Test as of 9 April 2022

Contents type: Spatial.   Period: 2003-2005

• n: 26
• Median: 8.5
• Quartile deviation: 1.5
• Range: 15
• Maximum possible: 14
• Male median: 8.5 (n = 24)
• Female median: 5.5 (n = 2)
• Resolution: 0.25 (0.35 if half points are frequently given)

Correlation of Spatial Insight Test with other tests by I.Q. Tests for the High Range

Weighted average of correlations: 0.763 (N = 166, weighted sum = 126.74)

Conservatively estimated minimum g loading: 0.87

Ranking in above table is based on the unrounded correlations. All available data is present in this table, no tests are left out except for those with less than 3 score pairs. All known pairs are used, including possible floor/ceiling scores or outliers.

Correlation of Spatial Insight Test with tests by others

Weighted average of correlations: 0.762 (N = 36, weighted sum = 27.43)

Ranking in above table is based on the unrounded correlations. All available data is present in this table, no tests are left out except for those with less than 3 score pairs. All known pairs are used, including possible floor/ceiling scores or outliers.

Please be aware that correlations with these external tests are in most cases affected (depressed, typically) by one or more of the following: (1) Little overlap with the object test because of the much lower ceilings and inherent ceiling effects of the tests used in regular psychology; (2) Candidates reporting scores selectively, for instance only the higher ones while withholding lower ones; (3) Candidates reporting, or having been reported by psychometricians, incorrect scores.

Estimated loadings of Spatial Insight Test on particular item types

These are estimated g factor loadings, but against homogeneous tests (containing only particular item types) as opposed to non-compound heterogeneous tests. Although tending to surprise the lay person, it is not uncommon for tests to have high loadings on item types they do not actually contain themselves. Such loadings reflect the empirical fact that most tests for mental abilities measure primarily g, regardless of their contents; that the major part of test score variance is caused by g, and only a minor part by factors germane to particular item types. It is of key importance to understand that this is a fact of nature, a natural phenomenon, and not something that was built into the tests by the test constructors.

N = 189

Compound tests have been left out of this table to avoid overlap.

Balanced g loading = 0.74

National medians for Spatial Insight Test

For reasons of privacy, only countries with 2 or more candidates are included in this table. Ranking is based on the medians, and then alphabetic.

Correlation with national I.Q.'s of Spatial Insight Test

Correlation of this test with national average I.Q.'s published by Lynn and Vanhanen:

• r = 0.13 (n = 25)

Correlation of Spatial Insight Test with personal details

Estimated g factor loadings upward and downward of particular scores

In parentheses the number of score pairs on which that estimated g factor loading is based. The goal of this is to verify the hypothesis that g becomes less important, accounts for a smaller proportion of the variance, at higher I.Q. levels. The mere fact of restricting the range like this also depresses the g loading compared to computing it over the test's full range, so it would be normal for both values to be lower than the test's full-range g loading.

Reliability

• Split-half (odd-even) = 0.86
• Split-half (other division) = 0.79
• Cronbach's alpha = 0.83

Error

• Standard error = 1.3 raw score points

Scores by age

N = 26

Scores by year taken

r_{year taken × median score} = 0.87 (N = 26)

Robustness and overall test quality

• Robustness by chronological rank = 0.52
• Robustness by month = 0.52 (r_{raw scores × months} = 0.46)
• Quality = 0.606

Item analysis

Item statistics are not published as that would help future candidates. To detect bad items, answers and comments from candidates are studied, as well as, for each problem, the correlation with total score and the proportion of candidates getting it wrong (hardness of the item). Possible bad items are removed or revised, resulting in a revised version of the test.

[More statistical reports]