### sas >> factorial analysis

Hi My name is Sgio

I from Brazil

Who I made Principal Axis Factorin in SAS????

And who I made the KMO???

Thanks!!!

### sas >> factorial analysis

Are you interested in factor analysis in SAS? Virtually all the factor
analytic approaches will require PROC FACTOR. If you are asking
about Principal Factor Analysis, then PROC FACTOR does that too.

or the Knowledge Management Open.

HTH,
David
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### sas >> factorial analysis

The KMO is Kaiser-Meyer-Olkin!!! Who I made it is SAS???

In Brazil there is one researcher who speaks who Principal Factor
Analysis not is analysis factorial!!!

Sgio Henrique

### sas >> factorial analysis

Sergio,

I presume that by "Who I made it is SAS???" you mean to ask "How do I
obtain it in SAS?"

If that is correct, then take a look at
http://www.utdallas.edu/ ~nkumar/FactorExample.PDF

The KMO, according to that article, is shown in SAS as "Kaiser's Measure

Art
--------
On Sat, 6 Jan 2007 08:34:46 -0800, =?iso-8859-1?q?S=E9rgio_Henrique?=

### sas >> factorial analysis

<<<
or the Knowledge Management Open.

factor analysis program,

Here's a link to what I think he means, but I don't have time right now to figure out how to reply

http://www.ncl.ac.uk/iss/statistics/docs/factoranalysis.html

Peter

### sas >> factorial analysis

XXXX@XXXXX.COM yelled:

Maybe Kaiser's measure of sampling adequacy is called KMO in *one*
stat tool, but that is not a common designation. In SAS, using
PROC FACTOR, you would look for the MSA option.

Then what do you want? Straight, uncluttered factor analysis?
Alpha factor analysis? Principal component analysis? Iterated
principal factor analysis? Unweighted least-squares factor analysis?
Maximum likelihood (canonical) factor analysis? Image component
analysis? Harris component analysis? PROC FACTOR can do all
of these, and more. But I don't know which you mean.

I cannot tell if the problem here is language or jargon. By that,
I mean I cannot tell if the problem is our trying to translate between
Spanish and English, if if the problem is in trying to translate
between one set of names for statistical tools, and another set
of names.

Either way, I don't understand why you have to yell. We're a kind
of civil group here.

HTH,
David
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### sas >> factorial analysis

The following excerpts I copied from:

http://www.ats.ucla.edu/stat/sas/library/factor_ut.htm

Factor analysis as a generic term includes principal component
analysis. While the two techniques are functionally very similar and
are used for the same purpose (data reduction), they are quite
different in terms of underlying assumptions.

....

There are still other methods of estimating communalities available in
SAS. Interested readers should refer to SAS manual[4]. Some method
should be chosen, because SAS by default sets all prior communalities
to 1.0, which is the same as requesting a principal components
analysis. This default setting has caused misunderstanding among the
novice users who are not aware of the consequence of overlooking the
default settings. Many researchers claim to have conducted a common
factor analysis when actually a principal components analysis was
performed.

Hope this is what you mean,

Gerben

PS Se voce quer, eu posso tentar ajudar voce em portugues (that's what
they speak in Brazil, David) tambem.

### sas >> factorial analysis

Hi All!!!

How do I obtain the Cronbach`s Alpha in SAS??

Sgio Henrique

### sas >> factorial analysis

proc corr alpha;
var item1-itemk;

Paul R. Swank, Ph.D. Professor
Director of Reseach
Children's Learning Institute
University of Texas Health Science Center-Houston

-----Original Message-----
From: SAS(r) Discussion [mailto: XXXX@XXXXX.COM ] On Behalf Of Sgio Henrique
Sent: Wednesday, January 10, 2007 10:54 AM
To: XXXX@XXXXX.COM
Subject: Re: factorial analysis

Hi All!!!

How do I obtain the Cronbach`s Alpha in SAS??

Sgio Henrique

### sas >> factorial analysis

XXXX@XXXXX.COM replied:

Dang. Mea Culpa. Mary (maryidahosas) pointed this out to me also.
I got a glitch in my wetware: I was thinking this post was from Spain,
while the 'joint inclusion probabilities' post wqas from Brazil.

I do know the difference between Portuguese and Spanish, and I really
can find Brazil on a map. :-)

David
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Sales & Deals
http://shopping.msn.com/content/shp/?ctid=198 ,ptnrid=176,ptnrdata=200639

```I recently acquired SAS QC, and also have SAS Base and SAS Stat.  I
want to know how to run   a simple conjoint analysis with 5 attributes
at 4 x 4 x 3 x 2 x 2 levels i.e. 192 combinations for choice.

When I try and run this in the market research module in SAS Stat it

```

```Hi,

With this it's work.

Sthane.

%macro FACT(N=);
data fac;
FACT=1;
%If &N ne 0 %then %do I=1 %to &N;
FACT =FACT*&I;
%end;
run;
proc print label;
var FACT;
run;

%mend FACT;

MPRINT(FACT):   data fac;
MPRINT(FACT):   FACT=1;
SYMBOLGEN:  Macro variable N resolves to 0
MLOGIC(FACT):  %IF condition &N ne 0 is FALSE
MPRINT(FACT):   run;

NOTE: The data set WORK.FAC has 1 observations and 1 variables.
NOTE: DATA statement used:
real time           0.00 seconds
cpu time            0.00 seconds

MLOGIC(FACT):  Ending execution.

-----Message d'origine-----
De : SAS(r) Discussion [mailto: XXXX@XXXXX.COM ] De la part de
Elmaache, Hamani
Envoy: jeudi 6 janvier 2005 22:24
:  XXXX@XXXXX.COM
Objet : Problem with macro: FACTORIAL

I'm trying to write this small macro:

calculate N! Example if N=4  we will have 1*2*3*4=24 =4!

The following macro very well when N is not zero, but when N=0 It doesn't
work. Can someone help. Thanks a lot.

%macro FACT(N=); %*--------------------------------------------------------;
%* Return N! Example if N=4  we will have 1*2*3*4=24 =4!  ;
%*--------------------------------------------------------;
data fac;
FACT=1;
%If &N=0 %then   FACT=1;
%do I=1 %to &N;
FACT =FACT*&I;
%end;
proc print label;
var FACT;
run;

%mend FACT;

%FACT(N=4);
%FACT(N=0);
```

```I am currently building an experimental design in the FS industry that is a=
=
5x3x2^2 design (that is 1 factor with 5 levels, 1 with 3 and 2 with 2 =
levels).

This creates a full factorial design with 60 cells and the question has bee=
n=
asked if we can reduce this design whilst still getting learnings.=20

Whilst I know there are some standard design matrices available, I'm not =
sure how (or if!) a design such as this can be reduced to a =
lesser-fraction=3F

If so, in the absence of licensing IML/QC in SAS, how could I go about=3F

Thanks

Peter Mackay | Senior Manager - Customer Analysis (Modelling)=20
Direct Marketing & Analytics | BT Financial Group
* 61-2-8253 6763 |* 61-2-8253 6980 |*  XXXX@XXXXX.COM
Voted Fund Manager of the Year AFR's Smart Investor Blue Ribbon Awards 2006
Also S&P's Manager of the Year 2006 for Australian Equity and Balanced Fund=
s=
(Neutral & Dynamic)

This message and any attachment is confidential and may be privileged or =
otherwise protected from disclosure.  If you have received it by mistake =
=
not copy the message or disclose its contents to anyone.

=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=
=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=
=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=
=3D=3D=3D
```

```Hi all:
I joined this group because I have come across a problem.I am planning to
run a 3 factorial design in a green house experiment. In this experiment
16 concentrations of Hormones will be applied with 2 Methods and tested on
2 Varieties(i.e. 16*2*2 combinations)

Factors:
Hormonal Concen.(1to16)=16
Number of Variety      = 2
Methods of application = 2
Number of replications = 3

Kindly help me in making the following:
-Hypothtical response data into a sas format e.g cards;
-sas satments for an analysis of variance and to compare means:

Rep    Var  Method    Conc.  #of roots
1 1 1 1 50
1 1 1 2 30
1 1 1 3 50
1 1 1 4 60
1 1 1 5 74
1 1 1 6 25
1 1 1 7 26
1 1 1 8 35
1 1 1 9 75
1 1 1 10 .
1 1 1 11 .
1 1 1 12 .
1 1 1 13 .
1 1 1 14 .
1 1 1 15 .
1 1 1 16 .
1 2 1 1 40
1 2 1 2 30
1 2 1 3 50
1 2 1 4 60
1 2 1 5 74
1 2 1 6 25
1 2 1 7 26
1 2 1 8 35
1 2 1 9 75
1 2 1 10 .
1 2 1 11 .
1 2 1 12 .
1 2 1 13 .
1 2 1 14 .
1 2 1 15 .
1 2 1 16 .
1 1 2 1 .
1 1 2 2 .
1 1 2 3 .
1 1 2 4 .
1 1 2 5 .
1 1 2 6 .
1 1 2 7 .
1 1 2 8 .
1 1 2 9 .
1 1 2 10 10
1 1 2 11 25
1 1 2 12 30
1 1 2 13 78
1 1 2 14 20
1 1 2 15 35
1 1 2 16 50
1 2 2 1 .
1 2 2 2 .
1 2 2 3 .
1 2 2 4 .
1 2 2 5 .
1 2 2 6 .
1 2 2 7 .
1 2 2 8 .
1 2 2 9 .
1 2 2 10 12
1 2 2 11 25
1 2 2 12 35
1 2 2 13 65
1 2 2 14 27
1 2 2 15 40
1 2 2 16 56
2 1 1 1 49
2 1 1 2 31
2 1 1 3 52
2 1 1 4 65
2 1 1 5 78
2 1 1 6 23
2 1 1 7 28
2 1 1 8 37
2 1 1 9 74
2 1 1 10 .
2 1 1 11 .
2 1 1 12 .
2 1 1 13 .
2 1 1 14 .
2 1 1 15 .
2 1 1 16 .
2 2 1 1 42
2 2 1 2 31
2 2 1 3 52
2 2 1 4 65
2 2 1 5 78
2 2 1 6 23
2 2 1 7 28
2 2 1 8 37
2 2 1 9 74
2 2 1 10 .
2 2 1 11 .
2 2 1 12 .
2 2 1 13 .
2 2 1 14 .
2 2 1 15 .
2 2 1 16 .
2 1 2 1 .
2 1 2 2 .
2 1 2 3 .
2 1 2 4 .
2 1 2 5 .
2 1 2 6 .
2 1 2 7 .
2 1 2 8 .
2 1 2 9 .
2 1 2 10 12
2 1 2 11 30
2 1 2 12 32
2 1 2 13 79
2 1 2 14 25
2 1 2 15 38
2 1 2 16 57
2 2 2 1 .
2 2 2 2 .
2 2 2 3 .
2 2 2 4 .
2 2 2 5 .
2 2 2 6 .
2 2 2 7 .
2 2 2 8 .
2 2 2 9 .
2 2 2 10 13
2 2 2 11 26
2 2 2 12 36
2 2 2 13 64
2 2 2 14 28
2 2 2 15 41
2 2 2 16 57
3 1 1 1 48
3 1 1 2 32
3 1 1 3 53
3 1 1 4 67
3 1 1 5 85
3 1 1 6 24
3 1 1 7 29
3 1 1 8 39
3 1 1 9 79
3 1 1 10 .
3 1 1 11 .
3 1 1 12 .
3 1 1 13 .
3 1 1 14 .
3 1 1 15 .
3 1 1 16 .
3 2 1 1 45
3 2 1 2 32
3 2 1 3 53
3 2 1 4 67
3 2 1 5 85
3 2 1 6 24
3 2 1 7 29
3 2 1 8 39
3 2 1 9 79
3 2 1 10 .
3 2 1 11 .
3 2 1 12 .
3 2 1 13 .
3 2 1 14 .
3 2 1 15 .
3 2 1 16 .
3 1 2 1 .
3 1 2 2 .
3 1 2 3 .
3 1 2 4 .
3 1 2 5 .
3 1 2 6 .
3 1 2 7 .
3 1 2 8 .
3 1 2 9 .
3 1 2 10 11
3 1 2 11 29
3 1 2 12 35
3 1 2 13 80
3 1 2 14 21
3 1 2 15 39
3 1 2 16 58
3 2 2 1 .
3 2 2 2 .
3 2 2 3 .
3 2 2 4 .
3 2 2 5 .
3 2 2 6 .
3 2 2 7 .
3 2 2 8 .
3 2 2 9 .
3 2 2 10 14
3 2 2 11 27
3 2 2 12 38
3 2 2 13 67
3 2 2 14 29
3 2 2 15 42
3 2 2 16 59
;
Run

Thank you very much for your cooperation and your help will be greatly
appreciated.

Best Regards
```