Your CIOS file request: Q-METHOD/06059110.011 hotline item

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Received:  by CIOS Mailer; Friday 5 Jun 2009 11:00:11
Date:         Fri, 5 Jun 2009 16:48:24 +0200
From:         Peter Schmolck 
Subject: Re: Analysis?
To:           Q-METHOD@LISTSERV.KENT.EDU
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Sam Hopper wrote:
> 
> Dear all
> I just have a couple of questions regarding my results and I wondered if
> anyone could help. The first is regarding eigenvalue's/% of variance
> explained - the prerotation values are:
> Factor  Eigenvalue      As Percentage   Cumulative percentage
> 1       20.78                61.12      61.12
> 2       1.74                 5.13       66.26
> 3       1.13                 3.34       69.60
> 4       1.00                 2.95       72.55
> 
> ect...

Given the 61% explained by the first, general factor, and negligible
amounts accounted for by 2, 3 etc., I can't imagine how one could come
to a conclusion other than: All persons say quite the same, except,
perhaps, for some idiosyncracies in one or another person's view. Your
4-factor rotation shows that you, unfortunately, did _not_ intend to
prove that there exists just exactly one single, general factor. ;(

Shouldn't we take up an earlier discussion on this list on strong vs.
weak factors? I would like to hear suggestions and experiences about
what could be helpful in the processes of statement and person selection
to strengthen the second, and the third etc. factors? 

> 
> but the post rotation ones are higher (see below), why is this, I'm going
> to have to explain it in a viva potentially.

That's not possible, or should not be possible, in fact. If the
cumulative percentages of the unrotated factors above and the %'s
explained variance below originate from the same analysis the figures
must be the same, i.e. 41 +   26 +  4 +  5 (=76) should add up to 72.55,
within rounding error. Even if you rotated more than 4 factors but kept
only 4, the sum of expl. variances could be smaller only but not larger
than the cumulative variance explained by the first 4 unrotated factors. 


> 
>  QSORT             1         2         3         4
> 
>   1 1            0.4356    0.6995X   0.1473   -0.1207
>   2 2            0.6738X   0.4643   -0.0180    0.1879
>   3 3            0.7053X   0.5243    0.0358    0.0964
>   4 4            0.5475    0.6437X  -0.1134   -0.1321
>   5 5            0.1918    0.6030X   0.3802   -0.0802
>   6 6            0.5815    0.6357X   0.0655    0.0106
>   7 7            0.8032X   0.3382    0.0457    0.2553
>   8 8            0.5793X   0.5234   -0.0133    0.0006
>   9 9            0.7499X   0.3172   -0.0290    0.3484
>  10 10           0.6242X   0.5898    0.0382    0.0342
>  11 11           0.6167X   0.4980    0.1298   -0.0137
>  12 12           0.7740X   0.3658    0.0986    0.2421
>  13 13           0.3465    0.4923X  -0.0391    0.2337
>  14 14           0.6139X   0.5119   -0.0139    0.0914
>  15 15           0.5519    0.6386X   0.2492   -0.1189
>  16 16           0.7346X   0.4022    0.1266    0.2470
>  17 17           0.8324X   0.2080    0.1408    0.4370
>  18 18           0.8249X   0.3016    0.1740    0.3439
>  19 19           0.7487X   0.4959    0.1330    0.0894
>  20 2800         0.6644X   0.4046    0.1106    0.2713
>  21 2809         0.0840    0.2934X   0.9208X   0.0424
>  22 2830         0.8255X   0.2794    0.0717    0.3035
>  23 2876         0.7728X   0.4232    0.1197    0.1627
>  24 2878         0.6264X   0.4768    0.1398    0.0909
>  25 2880         0.2799    0.7442X   0.2099   -0.1633
>  26 2884         0.6981X   0.5118    0.0937    0.0570
>  27 29 21        0.3420    0.7810X   0.1600   -0.2195
>  28 30 74        0.6144X   0.6092    0.0311    0.0211
>  29 3120         0.7232X   0.4899    0.0517    0.0845
>  30 3357         0.6375X   0.5772    0.1268   -0.0659
>  31 3371         0.6214X   0.4536    0.2503   -0.0161
>  32 3380        -0.5689X   0.4873    0.0069   -0.8105X
>  33 3382         0.7587X   0.3588   -0.0038    0.2617
>  34 3383         0.6317X   0.4697    0.2232    0.2220
> 
>  % expl.Var.         41        26         4         5
> 
> Secondly, I would like to look at subgroups within my data, but dont want
> to delete sorts from the file to do this. Is there a way of "ignoring"
> certain participants sorts or making a new file (with copied data) so I can
> delete the unwanted sorts?

No technical problem: make a backup copy of your .dat, and then edit the
.dat (with the notepad editor) and delete unwanted cases, and don't
forget to adjust the no of cases in the first record. However, selection
of subgroups should not be based on the same data that are used for
analysis. For instance, you would get contrieved results if you form
subgroups for new analyses runs by way of the factor loadings of
preceding analyses. 

Peter

-- 
Peter Schmolck   http://www.unibw.de/paed/esf-en/pers/schmolck