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  #1  
Old 05-04-2012
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Stats What statistical analysis to compare these two groups?

Self made.
=======

A researcher has designed a retrospective study, where patients undergoing laparoscopic and open operations for right hemicolecomy are compared. He has identified 30,000 patients records from National Inpatient Sample Database and created similar groups of patients treated by laparoscopic (N=15,000) or open (N=15,000) approach with matching demographical characteristics. Within the laparoscopic group, 5% died and within open 15% died. if he wants to compare the immediate perioperative outcomes for mortality within these two groups, what statistical test should he use?

a. Fisher's exact test
b. Paired T test
c. Chi-Square test
d. ANOVA
e. Two-Sample T test
f. Relative Risk
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  #2  
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chi square because of the percentages?
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relative risk?
he wants to compare the same outcome [mortality] but in different procedures... open surgery is 3 x times more likely to die
although relative risk is associated with cohort, which is a PROspective study, dunno :S

whats the answer please , pm if u dont want to post it here now...
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Dear DocSikorski

the correct answer is NONE!
I know that you created this question...

a. Fisher's exact test No for matched pairs
b. Paired T test no for inference in proportions/rates
c. Chi-Square test NO for matched pairs
d. ANOVA no for inference in proportions/rates
e. Two-Sample T test no for inference in proportions/rates
f. Relative Risk THIS is NOT a TEST.

you should re-write the question not using the "matched" assumption

good luck to all!
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Quote:
Originally Posted by bebix View Post
Dear DocSikorski

the correct answer is NONE!
I know that you created this question...

a. Fisher's exact test No for matched pairs
b. Paired T test no for inference in proportions/rates
c. Chi-Square test NO for matched pairs
d. ANOVA no for inference in proportions/rates
e. Two-Sample T test no for inference in proportions/rates
f. Relative Risk THIS is NOT a TEST.

you should re-write the question not using the "matched" assumption

good luck to all!
bebix dear bebix... thank u for still hanging around the forum or even if suddenly seeing this
great explanation

good luck to u in whatever u are doing now these days
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  #6  
Old 05-04-2012
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Quote:
Originally Posted by bebix View Post
Dear DocSikorski

the correct answer is NONE!
I know that you created this question...

a. Fisher's exact test No for matched pairs
b. Paired T test no for inference in proportions/rates
c. Chi-Square test NO for matched pairs
d. ANOVA no for inference in proportions/rates
e. Two-Sample T test no for inference in proportions/rates
f. Relative Risk THIS is NOT a TEST.

you should re-write the question not using the "matched" assumption

good luck to all!
uhm...
why not?

to compare apples to apples you have to have groups matched....
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I believe, that when you are able to write a good question - you really aced the topic.

Tests are my weak area, but I tried to make a good one
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Quote:
Originally Posted by DocSikorski View Post
uhm...
why not?

to compare apples to apples you have to have groups matched....
hahaha...yes, and for that you need to use

Mc Nemar test or Logistic regression for matched p. test with robust standard errors, hahahaha...

so, this is not only apple vs apple...this is apple vs apple´s sister!, hahaha

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Quote:
Originally Posted by bebix View Post
hahaha...yes, and for that you need to use

Mc Nemar test or Logistic regression for matched p. test with robust standard errors, hahahaha...

so, this is not only apple vs apple...this is apple vs apple´s sister!, hahaha

That's why reviewers of the papers still have their jobs =)
haha
=============

Multiple regression analysis will work for not matched groups, where all the comorbidites and risks, prior to surgery can be weighted individually to estimate the effect on the outcome...

For matched groups: e.g. young patients with 0-1 comorbidites (low illness severity) of same races/ethnicity, gender and diagnosis (e.g. colon cancer will be most appropriate for right hemicolectomy, as I used in the question) Chi-square will work just fine (i used it several times), if there were less than 10pts that died in each, we could use Fisher's exact test, but thats kinda sample size that you don't wont to make a paper of haha
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Last edited by DocSikorski; 05-04-2012 at 11:46 AM.
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Note:
If you have only nominal variable do chi-square,if you have only interval variable go for correlation,one nominal and one interval go for t-test,but if you have more than 2 variables (at least one of each) go for anova
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Quote:
Originally Posted by DocSikorski View Post
That's why reviewers of the papers still have their jobs =)
haha
=============

Multiple regression analysis will work for not matched groups, where all the comorbidites and risks, prior to surgery can be weighted individually to estimate the effect on the outcome...

For matched groups: e.g. young patients with 0-1 comorbidites (low illness severity) of same races/ethnicity, gender and diagnosis (e.g. colon cancer will be most appropriate for right hemicolectomy, as I used in the question) Chi-square will work just fine (i used it several times), if there were less than 10pts that died in each, we could use Fisher's exact test, but thats kinda sample size that you don't wont to make a paper of haha
hahaha...multiple regression (in this case logistic regression, which is part of the family of GLM) and weighted = with means marginal regression with sandwich estimation of the variance (robust SE)

So...anyone of your alternatives wasnt correct...dont worry, Im a Biostatistician

and X2 does not work...maybe is time to go back to the books
this is the bible for categorical analysis:

http://www.amazon.com/Statistical-Me...6164393&sr=8-1


good luck!

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Quote:
Originally Posted by irakly View Post
Note:
If you have only nominal variable do chi-square,if you have only interval variable go for correlation,one nominal and one interval go for t-test,but if you have more than 2 variables (at least one of each) go for anova

chi2 works only for independent samples
in case of matched data, you must use McNamer test.

good luck!
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  #13  
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Thanks, I might ask my supervisor to order it...
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