Suggest book for Logistic Regression
I want to buy an intro. book on logistic regression. I am encountering cases of experimentation that we need to do with ordinal, nominal, binary responses. One important thing is sample size (i.e., number of experimental units, or repetitions for the experiment), so I would like the book to address this issue, or you could recommend articles that deal with sample size calculation. Is Hosmer and Lemeshow a good INTRO. book? By the way, I am an engineer not a statistician. Lenin Sent via Deja.com http://www.deja.com/ Before you buy. === This list is open to everyone. Occasionally, less thoughtful people send inappropriate messages. Please DO NOT COMPLAIN TO THE POSTMASTER about these messages because the postmaster has no way of controlling them, and excessive complaints will result in termination of the list. For information about this list, including information about the problem of inappropriate messages and information about how to unsubscribe, please see the web page at http://jse.stat.ncsu.edu/ ===
Re: Control limits for machine downtime
In article <[EMAIL PROTECTED]>, Till Siebert <[EMAIL PROTECTED]> wrote: > [EMAIL PROTECTED] wrote: > > > We track a metric that consists of the fraction of hours that a machine > > was not running during a week. The numerator is the number of hours > > not running and the denominator is the number of hours running plus the > > hours not running. This is a weekly metric. I wish to calculate > > control limits on this metric such that I can pinpoint if in a > > particular week the machine is out of control. What is the > > distribution of this statistic so that I can calculate the lower and > > upper limits? or should I just estimate the distribution with > > historical data and calculate the limits from there? What do you > > recommend. > > Fractions are B distributed, at least if you have a small sample number. > You can calculate a confidence interval around a long time mean and > compare the measure of a week with it and so decide whether its fraction > of non-running time is exorbitantly high or low (outside the CI). Such a > decision would be mathematically exact I think. Maybe it is also possible > to replace B with an approximately similar N which > is easier to handle; that depends on whether the number of hours in a week > is hight enough and, I´m not sure now, whether such an approximation is > useful at all (depends on similarity of N and high sample number B). > > Bye, Till I thought of using a binomial distribution but it did not seem right to me. I am more inclined to think it is one of those maintenance distributions such as weibull, etc. The thing is that I am combining two measures in one: I am combining time to repair and the frequency of failure. Thus, if in a week the machine goes down twice and it takes 2 hours to repair, then my total downtime is 4 hours. Then what I am tracking is a fraction: 4hours/total production time. Who knows what distribution this follows? Is it the binomial? Lenin > Sent via Deja.com http://www.deja.com/ Before you buy. === This list is open to everyone. Occasionally, people lacking respect for other members of the list send messages that are inappropriate or unrelated to the list's discussion topics. Please just delete the offensive email. For information concerning the list, please see the following web page: http://jse.stat.ncsu.edu/ ===
Control limits for machine downtime
We track a metric that consists of the fraction of hours that a machine was not running during a week. The numerator is the number of hours not running and the denominator is the number of hours running plus the hours not running. This is a weekly metric. I wish to calculate control limits on this metric such that I can pinpoint if in a particular week the machine is out of control. What is the distribution of this statistic so that I can calculate the lower and upper limits? or should I just estimate the distribution with historical data and calculate the limits from there? What do you recommend. Lenin Sent via Deja.com http://www.deja.com/ Before you buy. === This list is open to everyone. Occasionally, people lacking respect for other members of the list send messages that are inappropriate or unrelated to the list's discussion topics. Please just delete the offensive email. For information concerning the list, please see the following web page: http://jse.stat.ncsu.edu/ ===
Re: Sample Size for an Audit
Thanks for the responses, in regards to the article you are offering (Chendrix), yes I would be interested in receiving it. My fax is 787 819-6670. Your e-mail does not work. In article <865u5l$7h6$[EMAIL PROTECTED]>, [EMAIL PROTECTED] wrote: > In any situation of this sort, the amount of data you > need is related to the amount of variation you expect > to find in the data... and is also related to "how close > do you want your answer to be to the truth" and also > with what probablity do you want to be that close to the > truth. By truth I mean "true average response" or the > population average. Statistical sampling theory is usually > founded on taking a small sample from a large (infinite) > population so that the sample does not "disturb" the > population. If the sample size is a significant fraction > of the entire population (as it will be in this instance, > with only 20 people in the population), then a correction > is needed to the usual formula for determining the correct > sample size. I don't have that formula/correction at > hand, but if you want it (or want a little paper I wrote > on this) let me know at [EMAIL PROTECTED] If you > want the paper, I'll need a fax number to send it to... > it is not digitized. If the response you are measuring > is a "pass/fail" response, that makes life easier because > we can estimate the standard deviation quickly and > painlessly. When all is said and done, with a population > of only 20, the sample will need to be a large fraction of > the population. Perhaps as many as 10 or 12. > Charlie H. > > In article <86536f$j77$[EMAIL PROTECTED]>, > [EMAIL PROTECTED] wrote: > > We are going to do a quality system audit (like ISO 9000). How do I > > choose the sample size for a particular group of people? Let's say > > that there are 20 supervisors and I will audit their knowledge of SPC, > > how many should I choose for the audit? > > > > Sent via Deja.com http://www.deja.com/ > > Before you buy. > > > > Sent via Deja.com http://www.deja.com/ > Before you buy. > Sent via Deja.com http://www.deja.com/ Before you buy.
Sample Size for an Audit
We are going to do a quality system audit (like ISO 9000). How do I choose the sample size for a particular group of people? Let's say that there are 20 supervisors and I will audit their knowledge of SPC, how many should I choose for the audit? Sent via Deja.com http://www.deja.com/ Before you buy.
