m******t
发帖数: 44 | 1 在用处理一个logistic regression(有多个解释变量 都是连续的），code 如下：
第一步
proc genmod data=datcom descend ;
model bidd = pdhdS1 pdnhS1 E age educyears D / dist=bin link=logit CovB;
by _Imputation_;
ods output ParameterEstimates=paraest CovB=covmat;
run;
这里生成了2个ods table.按理说，因为是multivariate inference,所以第二步
mianalyze应该采用如下code:
proc mianalyze parms=Paraest covb=covmat;
modeleffects intercept pdhdS1 pdnhS1 E age educyears D;
ods output ParameterEstimates=parameterest VarianceInfo=vinfo;
run;
在proc mianalyze输入data的时候，p... 阅读全帖 |
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b*******g
发帖数: 170 | 2 我以前碰到类似的问题，后来用PROC LOGISTIC做的，就能用MIANALYZE了。 |
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m******t
发帖数: 44 | 3 已经解决谢谢大家
在proc mianalyze的输入里面加上一个parainfo就行了 |
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s********a
发帖数: 154 | 4 在做一组数据的repeated analysis, 数据有missing value 用proc mi 生成10 sets
数据，然后proc mixed repeated analysis，接下来该怎样用proc mianalyze 得到
fixed effects 的p value？fixed effects 有categorical vars， 请牛人支招，谢谢
了 |
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k*********g
发帖数: 46 | 5 From Jonathan:
I have a question on the SAS proc MIANALYZE.
I have a dataset containing missing data, and I used proc MI (MCMC) to
generate 5 imputations
Then I ran logistic regression to the imputed dataset (by_imputation), and
then ran proc MIANALYZE to combine the results.
One of my variables, Education, was in 3 categories (
high school, >high school). The proc MIANALYZE give me the p-value of each
dummy comparing to the ref categories (HS vs HS vs
w... 阅读全帖 |
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H******r
发帖数: 2879 | 6 proc mianalyze.
or you can search Rubin "multiple imputation combining rules", it is kind of
intuitive. |
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t*********e
发帖数: 313 | 7 Thank you for the tips. I also received some help from SAS technical
suppport. Proc mianalyze can be used to ge combined means and std err, not
std dev. At this point, neither SAS nor Stata can produced two-way tables
using all the imputed data sets. I was told I have to average across all the
imputed data sets to get sample size.
Thanks! |
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s******h
发帖数: 539 | 8 用Proc MI + Proc logistc(w/by imputation option) + proc mianalyze |
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a****m
发帖数: 693 | 9 proc mi data=FitMiss noprint out=outmi seed=37851;
MIANALYZE procedure do imputation using non missing observation., |
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m****n
发帖数: 692 | 10 看SAS手册中的PROC MI和PROC MIANALYZE。很详细，做一般的MI足够。 |
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c*****a
发帖数: 808 | 14 在这看过几篇paper相关文章，希望对你有用
SAS缺失数据处理 Missing Data Imputation in SAS
Multiple Imputation for Missing Data: Concepts and New Development(Version 9
.0) (very good article)
An Introduction to Multiple Imputation Methods: HandlingMissing Data with
SAS V8.2
Imputation Techniques Using SAS Software for Incomplete Datain Diabetes
Clinical Trials
A SAS Macro for Single Imputation
quote:
"This paper reviews methods for analyzing missing data, including
basic concepts and applications of multiple imputation
te... 阅读全帖 |
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d******9
发帖数: 134 | 15 longitudinal study中，要用MANOVA分析四个treatment groups的某个continuous
outcome （看是否有tx effect, time effect, tx*time interaction）. 该outcome
有missing data, 但要求保留所有的records，那么就要用插值。
我用SAS中的PROC MI得出5个插值后的complete datasets, 但是不知道有没有办法用
PROC MIANALYZE combine 对5組数据分别MANOVA的结果（p-value）？如果这是不可行
的，那么我该怎么处理呢？随便挑选5組完整数据里面的一组来做MANOVA, 其他的忽略？
多谢多谢，在线等！ |
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a********4
发帖数: 2 | 17 感觉只能得到estimated coefficient 的p value,不会有type III fixed effects 的p
value. 我记得我查过，一个文献上是这么说的。
参考这个文章： Combining Type-III Analyses from Multiple Imputations
他们的macro可以combine， 但是貌似是针对anova的，不知道 mixed model 的是否可
以。你要是搞定了，麻烦通告一声，怎么搞定的。 谢了。 |
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