Notice: On April 23, 2014, Statalist moved from an email list to a forum, based at statalist.org.

[Date Prev][Date Next][Thread Prev][Thread Next][Date Index][Thread Index]

From |
daniel klein <klein.daniel.81@googlemail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: Multiple Imputation |

Date |
Mon, 7 Nov 2011 15:41:50 +0100 |

John, did you consult the help file, the pdf-manual, and/or other sources _before_ writing to Statalist as suggesteted in the FAQ (http://www.stata.com/support/faqs/res/statalist.html#before)? It seems, at least some of your questions can easily be solved using this material. You quote the error message, which is generally a good idea. However, all you probably need to solve your problem is already on your screen. Stata tells you to use -cd- to change your directory. So you should either type . cd <whatever directory you have write permission> directly, or, for more informartion . help cd Note that none of us can tell which directories you may write to and which not. Concerning your first question, I am not quite sure why you want to do univariate regression (I assume you mean univariate imputation using -regress-) when you have more than one variable with missing values. Univariate imputation is only appropriate if you have missing values in only one of your variables, as can be seen from the help file and pdf documentation. So you will have to use a multivariate method to impute your missing values. Questions about the propper number of imputations to be added are briefly discussed in the pdf manual. This number depends, besides other things, on how large your proporition of missing values is. If you do not want to go into greater detail here, the number should be something between 5 and 20, where 5 was a rule-of-thumbs for some time, manly because computers were slow and it would have been computationally to burdensome to do more. I think I am already starting to quote the pdf, so just start there. You will also find additional literature there. Concerinign -rseed()- please see the entry . help seed or follow the link to -[R] set seed- in the help file for -mi impute-. Personally, I do not believe the -seed- to be that important, if your are not running simulations, but others (knowing more about potential problems with computers generating "random" numbers) might well disagree here. I usually -set seed- only so I (and others) can replicate my results, and for thta purpose you may simply set your seed 42 (or any number). Note that there is an ado -setrngseed- by Antoine Terracol and Bill Gould, available from SSC that allows you to set "ture" random numbers. Best Daniel -- I am having a problem with -mi-. I am using Stata version 11.2. [...] Firstly, after registering variables with missings as imputed and registering other variables as normal, what variables do i include into the univariate regression? All variables in the data set? Or just the variables i need for a specific model? Because including all the imputed variables as well as the normal variables into the regression brings up a mesage that says : "Option add( ) is required when no imputation exist." How do i specify what number to have in add( ) and rseed( )? This leads me to use only one of the registered imputated variables and all the registered normal variables in the univariate regression. I get this message afterwards: "Could not find a filename for temporary flongsep file. I tried _mitmpfile1.dta through _mitmpfile200.dta. Peharps you do not have write permission in the current directory . This may occur, for example, if you started Stata by clicking directly on the Stata executable on a netweork drive. You should make sure you have written permission for the current directory or use cd to change to a directory that has write permission. Use pwd to determine you current directory." I dont understand how to change to a directory that has write pwermission. * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**Follow-Ups**:**RE: st: Multiple Imputation***From:*John Ebireri <j.ebireri.1@research.gla.ac.uk>

- Prev by Date:
**st: Bias corrected p-values after bootstrap** - Next by Date:
**Re: st: macro of macros?** - Previous by thread:
**st: RE: RE: Multiple Imputation** - Next by thread:
**RE: st: Multiple Imputation** - Index(es):