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I have a data set in which I have the date of joining of employees, age, and the date of leaving , also i have the dataset with current employees,so should I combine these two datasets or should I carry on with my analysis of already left employees, also i still dont understand properly time variable and status variable. if i can find out attrition based on gender of the employees, i have have their performance ratings as well. If you can please help me out with this, i will be highly obliged.

Thanks

Neal

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  • $\begingroup$ Although time is an essential part of any survival analysis, "status" is not. Would you mind clarifying for us what you mean by "status variable"? $\endgroup$ – whuber Jun 19 '15 at 12:40
  • $\begingroup$ Hello!! By status I mean the event variable , like if the company has adopted a measure for controlling attrition, then number of employees who left the company after 6 months of that measure. $\endgroup$ – Neal Jun 22 '15 at 4:49
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By your description I believe that you are trying to estimate the probability of a employee leave/stay the company after, eg, 6 months, 1 year, and so on.

So, all your employees will count, actives and non-actives. For survival analysis you need 2 variables: one referring time (quantitative) and the other referring the status active/non-active (binary variable).

For each employee, day 0 is when they start working in the company. If an employee leaves after 6 months (180 days), then you mark it as non-active. Otherwise the employee is considered active and you have to censor them at the last known day of work (today's date - start date).

I usually do survival analysis using days as a unit. Maybe for your is better using months.

After this first analysis you can start stratifying by gender and study if both survival distributions have the same behavior (you can use a Logrank test).

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  • $\begingroup$ Thanks Yohana I have a clear understanding now. I peformed a survival analysis in Rattle, I am getting a concordance of .67 , R square of .04, concordance I understand but what about the R square value, as it is very low. Also if you can tell me a book I should read , or a better software for doing it, Thanks a lot for your help $\endgroup$ – Neal Jun 22 '15 at 4:55
  • $\begingroup$ You are welcome! Well, you will see that all software gives you a lots of measures. About the R square take a quick look in apha.confex.com/apha/134am/techprogram/paper_135906.htm. Books, for survival I have "a bible" which is extremely big "Survival Analysis - Kleinbaum" springer.com/us/book/9781441966452. But I would suggest you to take a look to these 2 dictionaries "The Concise Encyclopedia of Statistics - Yadolah Dodge" and "THE CAMBRIDGE DICTIONARY OF Statistics - B. S. EVERITT". $\endgroup$ – yohanna Jun 23 '15 at 6:47

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