Paul: out of interest, why do you think using imputation software will give you better results, instead of just, say, drawing m values from a normal distribution that follows the features of your variable?
Daniel On 6 Jun 2011, at 16:26, Paul von Hippel wrote: > To clarify: I have N cases of a single iid variable Y. n<N cases are missing > the Y value at random. There are no Xs to predict Y, and that rules out most > imputation software, including IVEware. What software is available? > > In practice imputation is useless in this situation, but it's important from > a theoretical point of view. > > Sent from my iPhone. > Please excuse my brevity. > > On Jun 6, 2011, at 4:56 AM, William Winkler <[email protected]> > wrote: > >> univariate imputation - there are additional methods besides the below two >> >> http://www.isr.umich.edu/src/smp/ive/ >> >> http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.96.3441 - >> documentation for slice software - need another url for the software >> >> >> >> >> >> From: Paul von Hippel <[email protected]> >> >> >> To: [email protected] >> >> >> Date: 06/06/2011 05:18 AM >> >> >> Subject: Univariate imputation >> >> >> Sent by: Impute -- Imputations in Data Analysis >> <[email protected]> >> >> >> >> >> >> >> It is common in simulations to impute data with only one variable, but most >> imputation software assumes that there are at least two variables. Is >> software available that carries out univariate imputation? |^^^^^^^^^^^^^^^^^|-|\___ | [====[\\\\\\\\]>------, |-||''|O\,_______ |._......,,......___________/=||_|__|...o] ""'(@)"(@)""""""""""(@)(@)++++(@)
