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Hello,
I need to find the agreement between previous studies on the elements of sustainability practice in campus. for example: I have 7 studies done by difference universities. Each of the 7 studies have difference elements but at the same time, some of the elements in these 7 studies are the same. Thus, I've list out all the elements and need to narrow them down through the elements AGREED THE MOST between the 7 studies. Can I applied Cohen's Kappa in this example? or is there any better method can be use? Thank you in advance. Regard, Laila |
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Fariha
We need to know much more detail. In the 7 studies, do the common elements have the same variable names? If yes, you can probably use MATCH FILES <file list> /KEEP <varlist> . . where the varlist includes case ID as well. If no, you can always use RENAME VARIABLES to make sure all the common variables have the the same name(s). In either case File >> Save As . . and use a different file name. I can give further advice and assistance [off-list] if you send me (in complete confidence according to professional Codes of Conduct) the *.sav files and any relevant documentation (eg questionnaire or output from: Display Labels for each of the *.sav files). John F Hall (Mr) [Retired academic survey researcher] Email: [hidden email] Website: www.surveyresearch.weebly.com SPSS start page: www.surveyresearch.weebly.com/1-survey-analysis-workshop -----Original Message----- From: SPSSX(r) Discussion [mailto:[hidden email]] On Behalf Of fariha Sent: 28 September 2015 06:03 To: [hidden email] Subject: Agreement between studies Hello, I need to find the agreement between previous studies on the elements of sustainability practice in campus. for example: I have 7 studies done by difference universities. Each of the 7 studies have difference elements but at the same time, some of the elements in these 7 studies are the same. Thus, I've list out all the elements and need to narrow them down through the elements AGREED THE MOST between the 7 studies. Can I applied Cohen's Kappa in this example? or is there any better method can be use? Thank you in advance. Regard, Laila -- View this message in context: http://spssx-discussion.1045642.n5.nabble.com/Agreement-between-studies-tp57 30679.html Sent from the SPSSX Discussion mailing list archive at Nabble.com. ===================== To manage your subscription to SPSSX-L, send a message to [hidden email] (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 [hidden email] (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 |
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Fariha has a small data matrix,derived from content analysis, covering 7 studies and presence or absence of 11 elements. Elements as cases, studies as variables: 1 1 1 1 1 1 1 1 1 1 1 1 1 0 1 1 1 0 1 1 1 0 0 1 0 1 1 1 0 0 1 1 1 1 1 0 0 1 0 0 1 0 0 0 1 0 0 0 0 0 0 0 1 1 1 1 0 0 1 1 0 1 1 0 0 1 0 0 0 0 0 0 0 0 0 1 0
John F Hall (Mr) [Retired academic survey researcher] Email: [hidden email] Website: www.surveyresearch.weebly.com SPSS start page: www.surveyresearch.weebly.com/1-survey-analysis-workshop From: LAILATUFARIHA MAMAT [mailto:[hidden email]] OK. Thank you Sir for your respond On Tue, Sep 29, 2015 at 1:53 PM, John F Hall <[hidden email]> wrote:
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Maybe something more “significance test-y” is needed/wanted but why not begin by tabulating percent of studies with the characteristic and the co-occurrence of
pairs of characteristics. Gene Maguin From: SPSSX(r) Discussion [mailto:[hidden email]]
On Behalf Of John F Hall Fariha has a small data matrix,derived from content analysis, covering 7 studies and presence or absence of 11 elements.
Elements as cases, studies as variables: 1 1 1 1 1 1 1 1 1 1 1 1 1 0 1 1 1 0 1 1 1 0 0 1 0 1 1 1 0 0 1 1 1 1 1 0 0 1 0 0 1 0 0 0 1 0 0 0 0 0 0 0 1 1 1 1 0 0 1 1 0 1 1 0 0 1 0 0 0 0 0 0 0 0 0 1 0
John F Hall (Mr) [Retired academic survey researcher] Email:
[hidden email]
Website:
www.surveyresearch.weebly.com
SPSS start page:
www.surveyresearch.weebly.com/1-survey-analysis-workshop
From: LAILATUFARIHA MAMAT [[hidden email]]
OK. Thank you Sir for your respond On Tue, Sep 29, 2015 at 1:53 PM, John F Hall <[hidden email]> wrote:
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In reply to this post by John F Hall
How subjective are the judgements in the measurement process?
Are the categories so clear that there is no need to check inter-judge consistency/reliability?
Art Kendall
Social Research Consultants |
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The judgement are dichotomous, either presence/absence. The categories are quite clear to see through the previous studies. Since I'm not doing a questionnaire, just my own study through each of them, I need a test to strengthen my data. I also need to narrowing the no. of elements selected. Thus, I'm thinking of using some test that have cut-off point. On Tue, Sep 29, 2015 at 11:17 PM, Art Kendall [via SPSSX Discussion] <[hidden email]> wrote: How subjective are the judgements in the measurement process? |
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In reply to this post by Maguin, Eugene
I have tabulated the percent of studies with the characteristic and the co-occurrence of pairs of characteristics. Somehow, I got feedback that the analysis is not strong enough when I present them. I also need to narrow down the elements. Thus, I really need some test that have cut-off points. On Tue, Sep 29, 2015 at 9:23 PM, Maguin, Eugene [via SPSSX Discussion] <[hidden email]> wrote:
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I think you want to rearrange your data into decreasing rows and
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columns in order to look at it. Then reduce it, as below, and show the reduced table with the commentaries. Studies as cases: rows and columns rearranged. ===========11 elements====================== 1 1 1 1 1 1 0 1 1 0 1 =9 1 1 1 1 1 1 1 1 0 1 0 =9 1 1 1 1 1 0 1 0 0 0 0 =6 1 0 1 1 1 1 1 0 0 0 0 =6 1 1 0 1 0 1 1 0 0 0 0 =5 1 1 1 0 0 0 0 0 0 0 0 =2 1 1 1 0 0 0 0 0 0 0 0 =2 ======================================= 7 6 6 5 4 4 4 2 1 1 1 The first piece of commentary is that there are 4 elements that exist in only one or two studies. Dismiss them. Then, there are two studies that have only two elements. Mention them and the two elements, and dismiss them. Final commentary: That leaves 5 studies with no element missing more than once. ===========7 elements======== (further rearranged) 1 1 1 1 1 1 1 =7 1 1 1 1 1 1 0 =6 1 1 1 1 1 0 1 =6 1 1 1 0 1 1 1 =6 1 1 0 1 0 1 1 =5 I think that the word for testing on this design, with this N, is "inappropriate" or "embarrassing." -- Rich Ulrich Date: Tue, 29 Sep 2015 20:28:53 -0700 From: [hidden email] Subject: Re: Agreement between studies To: [hidden email] I have tabulated the percent of studies with the characteristic and the co-occurrence of pairs of characteristics. Somehow, I got feedback that the analysis is not strong enough when I present them. I also need to narrow down the elements. Thus, I really need some test that have cut-off points. [snip] |
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"I think that the word for testing on this design, with this N,
is "inappropriate" or "embarrassing."" Sow's Ear NE Silk purse!!! --
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