| Date: | Thu, 29 Sep 2011 19:42:14 +0200 |
| Reply-To: | Marta García-Granero <mgarciagranero@gmail.com> |
| Sender: | "SPSSX(r) Discussion" <SPSSX-L@LISTSERV.UGA.EDU> |
| From: | Marta García-Granero <mgarciagranero@gmail.com> |
| Subject: | Re: statistical differences between products evaluation using
incomplete block design |
| In-Reply-To: | <005d01cc7e8b$a27d3410$e7779c30$@isracenter.com> |
| Content-Type: | text/plain; charset=ISO-8859-1; format=flowed |
Hi Alexandra, please address your questions to the whole list.
What do you mean by "help interpreting the results"? You should run a
UNIANOVA with your data as as showed you in the example I sent. I forgot
to add post-hoc pairwise comparisons, like Tukey, BTW.
Regards,
Marta GG
El 29/09/2011 11:39, Alexandra Chirilov escribió:
> Dear Marta,
>
> Could you be so kind in order to help me interpreting the results?
>
>
> -----Original Message-----
> From: SPSSX(r) Discussion [mailto:SPSSX-L@LISTSERV.UGA.EDU] On Behalf Of
> Marta García-Granero
> Sent: Thursday, September 29, 2011 12:17 PM
> To: SPSSX-L@LISTSERV.UGA.EDU
> Subject: Re: statistical differences between products evaluation using
> incomplete block design
>
> El 29/09/2011 9:53, Alexandra Chirilov escribió:
>> Dear list,
>>
>> I have a problem...one of our client wants to evaluate 6 products in a
> CLT!
>> We propose him a balance incomplete block design (BIBD) (3 products
>> per respondents). I generate a quite balance design (D-efficiency = 0.8).
>>
>> I have never used before BIBD (I used only complete design) and I
>> don't have any idea how to statistically compare the products'
>> evaluation? What statistical test should I use in order to say that
>> product A is better perceived than product B (e.g.: 8.97 significantly
> higher than 8.80)?
> Hi Alexandra:
>
> Time ago I managed to replicate the results for this balanced incomplete
> block design I found in a book, using SPSS:
>
> Fert. Bl.1 Bl.2 Bl.3 Bl.4 Bl.5
> F1 94 96 100 92 -
> F2 95 75 76 - 92
> F3 76 100 - 97 98
> F4 94 - 102 93 96
> F5 - 75 91 86 95
>
> * Dataset *
> data list list/Block Fert Yield (3 F8.0).
> begin data
> 1 1 94
> 2 1 96
> 3 1 100
> 4 1 92
> 1 2 95
> 2 2 75
> 3 2 76
> 5 2 92
> 1 3 76
> 2 3 100
> 4 3 97
> 5 3 98
> 1 4 94
> 3 4 102
> 4 4 93
> 5 4 96
> 2 5 75
> 3 5 91
> 4 5 86
> 5 5 95
> end data.
>
> *Analysis *.
> UNIANOVA
> Yield BY Fert Block
> /RANDOM = Block
> /METHOD = SSTYPE(1)
> /INTERCEPT = INCLUDE
> /DESIGN = Block Fert.
>
> It is important:
>
> - Use SSTYPE(1) instead of the default method - SSTYPE(3)
> - The order of both factors in "/DESIGN" (last line) is blocks first, then
> treatments
>
> HTH,
> Marta GG
>
> =====================
> To manage your subscription to SPSSX-L, send a message to
> LISTSERV@LISTSERV.UGA.EDU (not to SPSSX-L), with no body text except the
> command. To leave the list, send the command SIGNOFF SPSSX-L For a list of
> commands to manage subscriptions, send the command INFO REFCARD
>
>
=====================
To manage your subscription to SPSSX-L, send a message to
LISTSERV@LISTSERV.UGA.EDU (not to SPSSX-L), with no body text except the
command. To leave the list, send the command
SIGNOFF SPSSX-L
For a list of commands to manage subscriptions, send the command
INFO REFCARD
|