dat.bourassa1996.RdResults from 47 studies on the association between handedness and eye-dominance.
dat.bourassa1996The data frame contains the following columns:
| study | numeric | study number |
| sample | numeric | sample number |
| author | character | (first) author |
| year | numeric | publication year |
| selection | character | selection of subjects on the basis of eyedness or handedness |
| investigator | character | investigator (psychologist, educationalist, or other) |
| hand_assess | character | method to assess handedness (questionnaire or performance based) |
| eye_assess | character | method to assess eyedness (see ‘Details’) |
| mage | numeric | mean age of sample |
| lh.le | numeric | number of left-handed left-eyed individuals |
| lh.re | numeric | number of left-handed right-eyed individuals |
| rh.le | numeric | number of right-handed left-eyed individuals |
| rh.re | numeric | number of right-handed right-eyed individuals |
| sex | character | sex of the sample (combined, male, or female) |
The 47 studies included in this meta-analysis examined the association between handedness and eye-dominance (ocular dominance or eyedness). Results are given in terms of \(2 \times 2\) tables, indicating the number of left-handed left-eyed, left-handed right-eyed, right-handed left-eyed, and right-handed right-eyed individuals. Note that some studies included multiple (independent) samples, so that the meta-analysis included 54 samples in total. Also, for some studies, the combined data of the males and females are further broken down into the two subgroups.
In some studies, there was indication that the selection of subjects was not random with respect to handedness and/or eyedness. While this should not influence the size of the association as measured with the odds ratio, this invalidates those studies for assessing the overall percentage of left-eyed and left-handed individuals.
Handedness was assessed in the individual studies either based on a questionnaire or inventory or based on task performance. Eyedness was assessed based on various methods: E.1 methods are based on task performance, while E.2.a denotes assessment based on a questionnaire. The performance based methods could be further broken down into: E.1.a.i (monocular procedure with object/instrument held in one hand), E.1.a.ii (monocular procedure with object/instrument held in both hands), E.1.b (binocular procedure), E.1.c (a combination of the previous methods), and E.1.d (some other method).
Bourassa, D. C., McManus, I. C., & Bryden, M. P. (1996). Handedness and eye-dominance: A meta-analysis of their relationship. Laterality, 1(1), 5–34. https://doi.org/10.1080/713754206
psychology, odds ratios
### copy data into 'dat' and examine data
dat <- dat.bourassa1996
head(dat, 10)
#> study sample author year selection investigator hand_assess eye_assess mage lh.le lh.re rh.le
#> 1 1 1 Mills 1925 no other questionnaire E.1.d NA 93 17 130
#> 2 2 2 Downey 1927 yes psychologist questionnaire E.1.b 37 140 91 305
#> 3 2 2 Downey 1927 yes psychologist questionnaire E.1.b 37 74 57 158
#> 4 2 2 Downey 1927 yes psychologist questionnaire E.1.b 37 66 34 147
#> 5 3 3 Miles 1930 no psychologist questionnaire E.1.a.ii 22 16 14 43
#> 6 4 4 Quinan 1931 no other performance E.1.b 25 102 97 597
#> 7 5 5 Jasper 1932 yes psychologist questionnaire E.1.a.ii 20 17 14 38
#> 8 6 6 Lund 1932 no psychologist performance E.1.a.ii 20 10 2 52
#> 9 7 7 Eyre 1933 no psychologist performance E.1.a.ii 15 7 2 15
#> 10 8 8 Updegraff 1933 no psychologist performance E.1.a.ii 4 4 2 15
#> rh.re sex
#> 1 760 combined
#> 2 697 combined
#> 3 427 male
#> 4 270 female
#> 5 114 combined
#> 6 1898 combined
#> 7 80 combined
#> 8 170 combined
#> 9 169 combined
#> 10 38 combined
### load metafor package
library(metafor)
### calculate log(OR) and corresponding sampling variance with 1/2 correction
dat <- escalc(measure="OR", ai=lh.le, bi=lh.re, ci=rh.le, di=rh.re, data=dat, add=1/2, to="all")
head(dat, 10)
#>
#> study sample author year selection investigator hand_assess eye_assess mage lh.le lh.re rh.le
#> 1 1 1 Mills 1925 no other questionnaire E.1.d NA 93 17 130
#> 2 2 2 Downey 1927 yes psychologist questionnaire E.1.b 37 140 91 305
#> 3 2 2 Downey 1927 yes psychologist questionnaire E.1.b 37 74 57 158
#> 4 2 2 Downey 1927 yes psychologist questionnaire E.1.b 37 66 34 147
#> 5 3 3 Miles 1930 no psychologist questionnaire E.1.a.ii 22 16 14 43
#> 6 4 4 Quinan 1931 no other performance E.1.b 25 102 97 597
#> 7 5 5 Jasper 1932 yes psychologist questionnaire E.1.a.ii 20 17 14 38
#> 8 6 6 Lund 1932 no psychologist performance E.1.a.ii 20 10 2 52
#> 9 7 7 Eyre 1933 no psychologist performance E.1.a.ii 15 7 2 15
#> 10 8 8 Updegraff 1933 no psychologist performance E.1.a.ii 4 4 2 15
#> rh.re sex yi vi
#> 1 760 combined 3.4384 0.0768
#> 2 697 combined 1.2544 0.0228
#> 3 427 male 1.2512 0.0395
#> 4 270 female 1.2627 0.0545
#> 5 114 combined 1.0970 0.1613
#> 6 1898 combined 1.2061 0.0222
#> 7 80 combined 0.9257 0.1645
#> 8 170 combined 2.6130 0.5202
#> 9 169 combined 3.4906 0.6037
#> 10 38 combined 1.4976 0.7127
#>
### overall association between handedness and eyedness
res <- rma(yi, vi, data=dat, subset=sex=="combined")
res
#>
#> Random-Effects Model (k = 54; tau^2 estimator: REML)
#>
#> tau^2 (estimated amount of total heterogeneity): 0.4340 (SE = 0.1208)
#> tau (square root of estimated tau^2 value): 0.6588
#> I^2 (total heterogeneity / total variability): 89.08%
#> H^2 (total variability / sampling variability): 9.16
#>
#> Test for Heterogeneity:
#> Q(df = 53) = 355.7748, p-val < .0001
#>
#> Model Results:
#>
#> estimate se zval pval ci.lb ci.ub
#> 1.3135 0.1098 11.9597 <.0001 1.0982 1.5287 ***
#>
#> ---
#> Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
#>
predict(res, transf=exp, digits=2)
#>
#> pred ci.lb ci.ub pi.lb pi.ub
#> 3.72 3.00 4.61 1.00 13.77
#>