| Re: weighting for Services Provision Assessment data [message #10520 is a reply to message #10512] |
Mon, 01 August 2016 22:26   |
gizachew
Messages: 18
Registered: December 2015
Location: Australia
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Thanks so much Dr Assaf,
Yes, I did all the weighting for the facility and client and applied the svyset for the client vs facility merged data as my intention is to identify facility and client determinants of client satisfaction. In this regard, I created client satisfaction variable using polychoric pca for the 11 facets at X202 and then dichotomised into binary variable using the median as a cut point.
Now, your recommendation to include "singleunit(centered)" in the svyset helped me a lot.
1) However, I would remain grateful if you assist me on how to calculate Intraclass correlation coefficient (ICC) for the null model (empty model without covariates) and Akaike information criterion (AIC) for checking the model fitness. The estat icc and estat ic, respectively for ICC and AIC, recommended by the Stata manual 14 doesn't work for me.
2) I am also intended to create cluster level variable (facil is my cluster) by aggregating the individual client's response in each cluster/facil (1 -15 clients in the cluster). For this, I am using collapse command but not exactly sure for categorical variables. Do I need to include weighing during collapse?
For example, I created variables for "information on method use" and "privacy maintained" as follow yet not exactly sure which measure of centrality I have to use. I presume collapsing at mean or median could work for continuous variables such as waiting time and duration of consultation.
recode XF117_1 (8=.) (1=1 yes) (2=0 no), gen (metuse)
gen privmaintained=.
replace privmaintained=0 if OF110!=" "
replace privmaintained=1 if strpos(OF110,"AB")>0
recode X201 (998=.), gen (waitingtime)
collapse (mean)metuse privmaintained (median) waitingtime, by(FACIL)
Thanks in Advance
Gizachew
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