Hello,
I have data derived for 63 participants. The data is not normally distributed and when I compare the medians between groups, the value is usually 0. I gather data sets where there are frequent 0's is not an uncommon statistical problems. It was suggested to me that bootstrapping may be a solution to this problem. There are three groups of interest (n=10, 23, 30) which I want to compare on variables such as prior hospitalisation and imprisonment. I found a macro by Marta Gracia-Granero which estimates a sample mean. http://spssx-discussion.1045642.n5.nabble.com/Bootstrapping-in-SPSS-td1071984.html Is it possible to use bootstrapping to test the difference between three sample means or medians, and if so how can I do this in SPSS? My crude solution had been to omit values of 0 and just compare individuals with values above 0, but appreciate this is problematic. Any assistance is appreciated. Bob ===================== 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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I don't have access to SPSS right now, but I think something like the following will work (assuming your license includes the BOOTSTRAP module).
SET RNG=MT. BOOTSTRAP. ONEWAY Y BY group.
--
Bruce Weaver bweaver@lakeheadu.ca http://sites.google.com/a/lakeheadu.ca/bweaver/ "When all else fails, RTFM." PLEASE NOTE THE FOLLOWING: 1. My Hotmail account is not monitored regularly. To send me an e-mail, please use the address shown above. 2. The SPSSX Discussion forum on Nabble is no longer linked to the SPSSX-L listserv administered by UGA (https://listserv.uga.edu/). |
In reply to this post by bgreen
Bootstrapping certainly will not solve the problems you face:
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1) unclear hypotheses; 2) tiny Ns for making any sort of meaningful comparisons when you do not expect huge differences among three groups. One way to make sense about data with too many 0's is to make two statements: Compare the fractions of zeros; and compare the means among the non-zero subjects. Comparing the number of zeros is usually meaningful. When your small-N data may have an extreme number or two, comparing the means might not seem to give much sense even after you strip out the zeros. You have to consider the narrative that you can produce. What makes sense? - If they are similar (or different), what sort of graphic or presentation of numbers show what is going on? With the size of the Ns, you should start out *assuming* that important differences will not necessarily show up on testing; anything you get from a test will be a bonus. - When you have data that the means do not look particularly meaningful, which seems to be the case here, I do not think that bootstrapping the means will give a good statement, but it is not something that I have tried. -- Rich Ulrich > Date: Wed, 22 Oct 2014 07:10:39 +1000 > From: [hidden email] > Subject: bootstrapping difference between means > To: [hidden email] > > Hello, > > I have data derived for 63 participants. The data is not normally > distributed and when I compare the medians between groups, the value > is usually 0. I gather data sets where there are frequent 0's is not > an uncommon statistical problems. It was suggested to me that > bootstrapping may be a solution to this problem. There are three > groups of interest (n=10, 23, 30) which I want to compare on > variables such as prior hospitalisation and imprisonment. > > I found a macro by Marta Gracia-Granero which estimates a sample > mean. > http://spssx-discussion.1045642.n5.nabble.com/Bootstrapping-in-SPSS-td1071984.html > > Is it possible to use bootstrapping to test the difference between > three sample means or medians, and if so how can I do this in SPSS? > My crude solution had been to omit values of 0 and just compare > individuals with values above 0, but appreciate this is problematic. > > Any assistance is appreciated. > |
Hello Rich,
Thanks. The overall hypothesis was that the group who received the most support would have a lower re-incarceration rate and the purpose of the tests were simply to examine whether the groups differed in any significant way (e.g in terms of age, sex, previous hospitalisation days and frequency & previous imprisonment days and number etc). After removing the zeros I ran non-parametric analyses due to the non-normal distribution of the data. I hadn't considered examining fractions of zeroes, though did dichotomize some variables. Zero-inflated Negative Binomial Regression was another option that had been suggested. Thanks again Bob At 02:56 PM 22/10/2014, Rich Ulrich wrote: >Bootstrapping certainly will not solve the problems you face: >1) unclear hypotheses; >2) tiny Ns for making any sort of meaningful comparisons when you >do not expect huge differences among three groups. > >One way to make sense about data with too many 0's is to make >two statements: Compare the fractions of zeros; and compare the >means among the non-zero subjects. Comparing the number of zeros >is usually meaningful. When your small-N data may have an extreme >number or two, comparing the means might not seem to give much >sense even after you strip out the zeros. > >You have to consider the narrative that you can produce. What makes >sense? - If they are similar (or different), what sort of graphic >or presentation >of numbers show what is going on? With the size of the Ns, you should start >out *assuming* that important differences will not necessarily show up on >testing; anything you get from a test will be a bonus. > > - When you have data that the means do not look particularly meaningful, >which seems to be the case here, I do not think that bootstrapping the >means will give a good statement, but it is not something that I have tried. > >-- >Rich Ulrich > > > Date: Wed, 22 Oct 2014 07:10:39 +1000 > > From: [hidden email] > > Subject: bootstrapping difference between means > > To: [hidden email] > > > > Hello, > > > > I have data derived for 63 participants. The data is not normally > > distributed and when I compare the medians between groups, the value > > is usually 0. I gather data sets where there are frequent 0's is not > > an uncommon statistical problems. It was suggested to me that > > bootstrapping may be a solution to this problem. There are three > > groups of interest (n=10, 23, 30) which I want to compare on > > variables such as prior hospitalisation and imprisonment. > > > > I found a macro by Marta Gracia-Granero which estimates a sample > > mean. > > > http://spssx-discussion.1045642.n5.nabble.com/Bootstrapping-in-SPSS-td1071984.html > > > > Is it possible to use bootstrapping to test the difference between > > three sample means or medians, and if so how can I do this in SPSS? > > My crude solution had been to omit values of 0 and just compare > > individuals with values above 0, but appreciate this is problematic. > > > > Any assistance is appreciated. > > ===================== 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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