Re: Minitab vs. JMP
I've used JMP 3.2 mainly for survival analysis, very recently upgraded to JMP 4, performance degradation of the survival module was very disturbing. File 162541 records, stratification variable 6 levels, Kaplan-Meier procedure (univariate analysis), display separately one graph for each of the levels. JMP 3.2: Run procedure Summary table = 13 seconds Click to turn By_mode ON = 18 seconds (my eyes aren't very good) Run procedure Survival, from start click on command to final display = 5 seconds Total time required by JMP 3.2 = 36 seconds. JMP 4: Did not require to run Summary table, less mouse clicks. From start selecting Survival to final display total time required by JMP 4 = 21 minutes. I haven't looked at other procedures. I've no experience of Minitab. Vincent Ken wrote: Although I am currently a full time user of Minitab, I used JMP 3.x for 3 years before moving to Minitab. I would like to hear comments from users of JMP 4.0 comparing it to JMP 3 and maybe Minitab 13. What do you think of the changes? I'd also like to hear other Minitab vs JMP comments. What are your thoughts? Ken = Instructions for joining and leaving this list and remarks about the problem of INAPPROPRIATE MESSAGES are available at http://jse.stat.ncsu.edu/ =
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Re: Logistic Regression
Hi Ms. Howser Aside from the Hosmer and Lemeshow reference, an even more instructive beginning can be found in: David Kleinbaum. Logistic Regression: A Self-Learning Text. Springer Publications, 1994. Regards, Gary Winkel On Fri, 1 Sep 2000 22:56:26 - "Jennifer Howser" [EMAIL PROTECTED] writes: Hi everyone, My background is not statistics. I finished the first 2 levels of general statistics. I would like to purchase a logistic regression to learn on my own. I am looking for a book that is relatively easy to start with. If you have any recommendation, I really appreciate. Thanks = Instructions for joining and leaving this list and remarks about the problem of INAPPROPRIATE MESSAGES are available at http://jse.stat.ncsu.edu/ = = Instructions for joining and leaving this list and remarks about the problem of INAPPROPRIATE MESSAGES are available at http://jse.stat.ncsu.edu/ =
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Re: Logistic Regression
Jennifer Howser wrote: Hi everyone, My background is not statistics. I finished the first 2 levels of general statistics. I would like to purchase a logistic regression to learn on my own. I am looking for a book that is relatively easy to start with. If you have any recommendation, I really appreciate. Thanks you cant go past david kleinbaum's logistic regression: a self learning text sue = Instructions for joining and leaving this list and remarks about the problem of INAPPROPRIATE MESSAGES are available at http://jse.stat.ncsu.edu/ =
Re: Skewness and Kurtosis Questions
in article [EMAIL PROTECTED], christopher.mecklin at [EMAIL PROTECTED] wrote on 8/29/00 8:05 AM: Ronny, Kurtosis is poorly defined in almost every elementary stat textbook around. "Tailedness" and "peakedness" are both components of kurtosis. It is impossible to adequately explain kurtosis with just one component. A good reference that discusses this in much more detail is: DeCarlo, L.T. (1997). "On the meaning and use of kurtosis". Psychological Methods, 2, 292-307. I'm joining this thread late but i have to make a couple of comments: 1. the DeCarlo article is excellent; read it. why so many (including some of this thread) is confused about kurtosis is because most textbooks illustrate kurtosis with figures that vary not only kurtosis but also variance. if you control the variance to be the same and only vary kurtosis, the pictures look rather different and don't seem to have much to do with the peak. 2. in any discussion of the comparison of means and medians i have to throw in that wonderful fact that the mean and median can be at most one standard deviation apart. one of those lovely results that makes theoretical statistics so much fun. gary -- [EMAIL PROTECTED] = Instructions for joining and leaving this list and remarks about the problem of INAPPROPRIATE MESSAGES are available at http://jse.stat.ncsu.edu/ =