Sib-pair Command: pca


ClassAnalysis and data manipulation command
Namepca
Arguments [<quantitative trait 1> <quantitative trait 2> [...<quantitative trait N>]]

Carries out principal components analysis for the listed traits.

If a single integer (N) is given, this allows entry of the lower triangle of an N by N covariance matrix via the keyboard.

Example:

>> # Example dataset from R datasets package
>> # Originally from
>> # Statistical Abstracts of the United States 1975.(Urban rates).
>> set loc Murder qua
>> set loc Assault qua
>> set loc UrbanPop qua
>> set loc Rape qua
>> read cases inline
>> #ID           Murder Assault UrbanPop Rape 
>> Alabama       13.2   236     58       21.2 
>> Alaska        10     263     48       44.5 
>> Arizona       8.1    294     80       31   
>> Arkansas      8.8    190     50       19.5 
>> California    9      276     91       40.6 
>> Colorado      7.9    204     78       38.7 
>> Connecticut   3.3    110     77       11.1 
>> Delaware      5.9    238     72       15.8 
>> Florida       15.4   335     80       31.9 
>> Georgia       17.4   211     60       25.8 
>> Hawaii        5.3    46      83       20.2 
>> Idaho         2.6    120     54       14.2 
>> Illinois      10.4   249     83       24   
>> Indiana       7.2    113     65       21   
>> Iowa          2.2    56      57       11.3 
>> Kansas        6      115     66       18   
>> Kentucky      9.7    109     52       16.3 
>> Louisiana     15.4   249     66       22.2 
>> Maine         2.1    83      51       7.8  
>> Maryland      11.3   300     67       27.8 
>> Massachusetts 4.4    149     85       16.3 
>> Michigan      12.1   255     74       35.1 
>> Minnesota     2.7    72      66       14.9 
>> Mississippi   16.1   259     44       17.1 
>> Missouri      9      178     70       28.2 
>> Montana       6      109     53       16.4 
>> Nebraska      4.3    102     62       16.5 
>> Nevada        12.2   252     81       46   
>> NewHampshire  2.1    57      56       9.5  
>> NewJersey     7.4    159     89       18.8 
>> NewMexico     11.4   285     70       32.1 
>> NewYork       11.1   254     86       26.1 
>> NorthCarolina 13     337     45       16.1 
>> NorthDakota   0.8    45      44       7.3  
>> Ohio          7.3    120     75       21.4 
>> Oklahoma      6.6    151     68       20   
>> Oregon        4.9    159     67       29.3 
>> Pennsylvania  6.3    106     72       14.9 
>> RhodeIsland   3.4    174     87       8.3  
>> SouthCarolina 14.4   279     48       22.5 
>> SouthDakota   3.8    86      45       12.8 
>> Tennessee     13.2   188     59       26.9 
>> Texas         12.7   201     80       25.5 
>> Utah          3.2    120     80       22.9 
>> Vermont       2.2    48      32       11.2 
>> Virginia      8.5    156     63       20.7 
>> Washington    4      145     73       26.2 
>> WestVirginia  5.7    81      39       9.3  
>> Wisconsin     2.6    53      66       10.8 
>> Wyoming       6.8    161     60       15.6 
>> ;;;;
>> run
>> pca

Variable        Mean      Stand Dev  Correlations
---------- ------------ ------------ ---------------------
Murder           7.7880       4.3555 1.00
Assault        170.7600      83.3377 0.80 1.00
UrbanPop        65.5400      14.4748 0.07 0.26 1.00
Rape            21.2320       9.3664 0.56 0.67 0.41 1.00

Number of variables     =      4
No. usable observations =     50      ( 100.0%)

Variances for the principal components
           2.480     0.9898     0.3566     0.1734
Proportion of total variance due to each component
           0.620      0.247      0.089      0.043
Loadings of each variable on components
Murder     0.5359    -0.4182     0.3412     0.6492
Assault    0.5832    -0.1880     0.2681    -0.7434
UrbanPop   0.2782     0.8728     0.3780     0.1339
Rape       0.5434     0.1673    -0.8178     0.0890


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