Running examples in 'psychTools-Ex.R' failed
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> ### Name: holzinger.swineford
> ### Title: The raw and transformed data from Holzinger and Swineford, 1939
> ### Aliases: holzinger.swineford holzinger.raw holzinger.dictionary
> ### Keywords: datasets
> 
> ### ** Examples
> 
> data(holzinger.raw)
> psych::describe(holzinger.raw)
              vars   n   mean     sd median trimmed    mad min max range  skew
case             1 301 176.55 105.94    163  176.78 140.85   1 351   350 -0.01
school           2 301   0.48   0.50      0    0.48   0.00   0   1     1  0.07
grade            3 301   7.48   0.50      7    7.47   0.00   7   8     1  0.09
female           4 301   1.51   0.50      2    1.52   0.00   1   2     1 -0.06
ageyr            5 301  13.00   1.05     13   12.89   1.48  11  16     5  0.69
mo               6 301   5.38   3.45      5    5.32   4.45   0  11    11  0.09
agemo            7 301 161.26  12.22    159  160.24  11.86 136 199    63  0.72
t01_visperc      8 301  29.61   7.00     30   29.79   7.41   4  51    47 -0.25
t02_cubes        9 301  24.35   4.71     24   24.07   4.45   9  37    28  0.47
t03_frmbord     10 301  14.23   2.83     14   14.19   2.97   6  25    19  0.20
t04_lozenges    11 301  18.00   9.05     17   17.59  10.38   2  36    34  0.38
t05_geninfo     12 301  40.59  12.38     41   40.60  13.34   8  84    76  0.09
t06_paracomp    13 301   9.18   3.49      9    9.07   2.97   0  19    19  0.27
t07_sentcomp    14 301  17.36   5.16     18   17.58   5.93   4  28    24 -0.35
t08_wordclas    15 301  26.13   5.68     26   26.27   5.93  10  43    33 -0.21
t09_wordmean    16 301  15.30   7.67     14   14.62   7.41   1  43    42  0.86
t10_addition    17 301  96.28  25.06     94   95.76  25.20  30 171   141  0.25
t11_code        18 301  69.16  15.67     68   68.79  14.83  19 118    99  0.25
t12_countdot    19 301 110.54  20.25    110  109.86  19.27  61 200   139  0.53
t13_sccaps      20 301 193.47  36.33    195  193.18  35.58 100 333   233  0.20
t14_wordrecg    21 301 175.15  11.51    176  175.85  11.86 121 198    77 -0.84
t15_numbrecg    22 301  90.01   7.73     90   90.14   8.90  68 112    44 -0.09
t16_figrrecg    23 301 102.52   7.63    103  102.90   7.41  58 119    61 -0.94
t17_objnumb     24 301   8.23   4.92      8    7.85   4.45   0  26    26  0.86
t18_numbfig     25 301   9.41   4.50      9    9.24   4.45   0  20    20  0.28
t19_figword     26 301  14.04   4.08     14   14.29   4.45   3  20    17 -0.49
t20_deduction   27 301  26.89  19.33     26   25.85  20.76 -18  87   105  0.49
t21_numbpuzz    28 301  14.25   4.56     14   14.38   4.45   1  24    23 -0.31
t22_probreas    29 301  26.24   9.20     26   25.83  10.38   7  50    43  0.40
t23_series      30 301  18.14   9.14     19   17.95  10.38   1  40    39  0.10
t24_woody       31 301  24.27   4.74     25   24.36   5.93  11  35    24 -0.18
t25_frmbord2    32 145  15.65   3.09     16   15.76   2.97   5  23    18 -0.43
t26_flags       33 145  36.30   8.34     37   36.94   8.90  13  48    35 -0.64
              kurtosis   se
case             -1.36 6.11
school           -2.00 0.03
grade            -2.00 0.03
female           -2.00 0.03
ageyr             0.20 0.06
mo               -1.22 0.20
agemo             0.13 0.70
t01_visperc       0.31 0.40
t02_cubes         0.33 0.27
t03_frmbord       0.67 0.16
t04_lozenges     -0.91 0.52
t05_geninfo       0.00 0.71
t06_paracomp      0.08 0.20
t07_sentcomp     -0.55 0.30
t08_wordclas      0.28 0.33
t09_wordmean      0.82 0.44
t10_addition     -0.31 1.44
t11_code          0.44 0.90
t12_countdot      1.17 1.17
t13_sccaps        0.29 2.09
t14_wordrecg      1.83 0.66
t15_numbrecg     -0.21 0.45
t16_figrrecg      3.43 0.44
t17_objnumb       1.08 0.28
t18_numbfig      -0.57 0.26
t19_figword      -0.52 0.23
t20_deduction     0.16 1.11
t21_numbpuzz      0.10 0.26
t22_probreas     -0.23 0.53
t23_series       -0.75 0.53
t24_woody        -0.50 0.27
t25_frmbord2      0.45 0.26
t26_flags        -0.32 0.69
> data(holzinger.dictionary)
> holzinger.dictionary  #to see the longer names for these data (taken from Thompson)
                             Content
case                            case
school                        school
grade                          grade
female                         femal
ageyr                           agey
mo                                mo
agemo                          agemo
t01_visperc         VisualPerception
t02_cubes                      Cubes
t03_frmbord        t3_PaperFormBoard
t04_lozenges             t4_lozenges
t05_geninfo       GeneralInformation
t06_paracomp   PargraphComprehension
t07_sentcomp      SentenceCompletion
t08_wordclas      WordClassification
t09_wordmean             WordMeaning
t10_addition                Addition
t11_code                        Code
t12_countdot            CountingDots
t13_sccaps    StraightCurvedCapitals
t14_wordrecg         WordRecognition
t15_numbrecg       NumberRecognition
t16_figrrecg       FigureRecognition
t17_objnumb             ObjectNumber
t18_numbfig             NumberFigure
t19_figword               FigureWord
t20_deduction              Deduction
t21_numbpuzz        NumericalPuzzles
t22_probreas        ProblemReasoning
t23_series          SeriesCompletion
t24_woody         ArithmeticProblems
t25_frmbord2               Formboard
t26_flags                      Flags
                                                                           long
case                                                                         Id
school                                           School Pasteur  or Grant-White
grade                                                            Grade (7 or 8)
female                                             Gender (1= male, 2 = female)
ageyr                                                              age in years
mo                                                                       Months
agemo                                                            Age in months 
t01_visperc                    Visual perception test from Spearman VPT  Part O
t02_cubes             Cubes, Simplification of Brighams Spatial Relations Test 
t03_frmbord       Paper formboard-Shapes that can be combined to form a target 
t04_lozenges  Lozenges from Thorndike-Shapes flipped over then identify target 
t05_geninfo                                     General Information Verbal Test
t06_paracomp                                       Paragraph Comprehension Test
t07_sentcomp                                          Sentence Completion Test 
t08_wordclas                    Word clasification-Which word not belong in set
t09_wordmean                                                  Word Meaning Test
t10_addition                                             Speeded addition test 
t11_code                Speeded codetest-Transform shapes into alpha with code 
t12_countdot                                 Speeded counting of dots in shape 
t13_sccaps                     Speeded discrimation of straight and curved caps
t14_wordrecg                                             Memory of Target Words
t15_numbrecg                                           Memory of Target Numbers
t16_figrrecg                                            Memory of Target Shapes
t17_objnumb                         Memory of object-Number association targets
t18_numbfig                         Memory of number-Object association targets
t19_figword                           Memory of figure-Word association targets
t20_deduction                                            Deductive Math Ability
t21_numbpuzz                                                Math number puzzles
t22_probreas                                        Math word problem reasoning
t23_series                                   Completion of a Math Number Series
t24_woody                             Woody-McCall mixed math fundamentals test
t25_frmbord2                                     Revisionof t3-Paper form board
t26_flags                             Flags-possible substitute for t4 lozenges
> 
> #show suppression effects
> psych::setCor(t01_visperc + t05_geninfo + t08_wordclas ~ grade + agemo,data = holzinger.raw)
Error in nchar(tv[1, 21]) : 'nchar()' requires a character vector
Calls: <Anonymous> -> setCor.diagram -> multi.arrow
Execution halted