excellent, thanks both. I originally looked at that documentation but checked the "overview" section for details. I must have been rushed and didn't see "details". cheers
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i'd like to see some explanation and equations for this but the sas manual isn't clear. I know lifetest uses the Nelson-Aalen estimate, but i'm unsure about phreg Regarding phreg and estimating S(t) the manual says: "This method exponentiates the negative empirical cumulative hazard function to compute the survival function estimates. ....(Allison 2010). The product limit method is the default". thus it's an empirical estimate? but how are the covariates accounted for? I'd like to see some equations or a reference to persuade myself. The Allison reference is a sas book and doesn't give the detail there was a useful comment on sas communities where someone said: "You can only get the cumulated hazard function from phreg..... In the Cox-model the maximum-likelihood estimate of the cumulated hazard function is a step function ..." But without an estimate of the baseline hazard (which cox is not concerned with), how contrive the cumulative hazard for a set of covariates? thanks [edit: just to be clear: i know how to obtain cumulative hazard using phreg, i use a baseline statement etc, i just dont know exactly what it's doing]
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for what it's worth, i stumbled upon a couple of sources of info: -"sas performance tuning techniques" https://www.phuse.eu/blog/sas%c2%ae-performance-tuning-techniques [need to be a phuse member to access, most recommendations are common sense] -guy on this message board asks a similar Q, and ultimately the recommendation is to buy more RAM because it's cheap: https://www.developpez.net/forums/d1490127/logiciels/solutions-d-entreprise/business-intelligence/sas/sas-stat/proc-phreg-fragilite-effet-aleatoire-p-processus-comptage/
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this is a good question. I read a sas blog that suggested using "options nonotes;" to suppress notes in the log, but then you cannot evaluate convergence easily. edit: maybe it also helps to use proc printto to send the output and log to a file, rather than it filling up the log window etc i too am interested in what users think about solving the memory issue
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proc univariate would give you the max, use an ods statement to throw the value into a dataset. To get the max three values of a column (ie a variable) use proc rank: http://support.sas.com/documentation/cdl/en/proc/61895/HTML/default/viewer.htm#rank-overview.htm
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use proc glm and a random statement with 'inverse' option in the model statement to incorporate SE as weights? although anne whitehead says in her book on meta-analysis, section 4.2.4 on weighted LS regression, regarding SAS: "It should be noted that the standard error and test statistics displayed for the intercept parameter are incorrect for the required model, because they assume that var(εi) = σ2/wi, where σ2 is to be estimated from the data, instead of equal to 1. This will also be the case for other statistical packages." i'm not sure if this is helpful ....
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index or substr functions with an "if ... then delete" statement. That would be a crude way, i think there's a better way using other text functions that someone else will know
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the original source data are sas datasets or you convert them from something else? how are you importing the data into sas? the note in the log may be relevant for a subset of variables and you might want to figure out which ones they are. In which case you can modify the import (use the code generated by proc import that appears in the log). Maybe you have done these things already though ...
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you already have the 'ord' variable in the dataset. Thus, just put a format on it and then in proc report have eg: compute before ord;
line @1 ord $ord_f.;
endcomp; it won't fill in the rows in the dataset but i assume ultimately you want to display the output using eg proc report. Otherwise use a put statement with the format in the datastep
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if you just want to view the code you can right click on the .sas file, then 'open with' and chooseeg notepad. But to do anything with them you'll need sas of course
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sas technical support don't respond to technical statistical Q's like this (they have refused me before for this reason, they condiser it consultancy, fair enough). i'm not sure why you would consider GEE here. Survival analysis would make more sense (proc phreg) or logistic regression (proc logistic or proc genmod). Need a guesstimate of censoring rate etc to inform the best approach.
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thanks for replying to my query. I have the 'save settings on exit' option selected. Unfortunately the right mouse button (RMB) doesn't allow me to 'pin to taskbar'. That would be great. Maybe in the future it will allow it...
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