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Peru 2004 and 2007 [message #5443] Wed, 27 May 2015 17:23 Go to next message
kgrepin is currently offline  kgrepin
Messages: 1
Registered: July 2013

Online files listed for peru 2004 are coded PEXX51XX.* and for peru 2007 PEXX5AXX.*. However, when you actually download the 2007 data it comes back with the same file extensions as 2004 PEXX51XX.*.

I know these are continuous surveys so how should I treat these datasets. Is everything from 2004 really in 2007?

Thanks in advance,

Re: Peru 2004 and 2007 [message #5468 is a reply to message #5443] Thu, 28 May 2015 06:21 Go to previous messageGo to next message
Bridgette-DHS is currently offline  Bridgette-DHS
Messages: 2357
Registered: February 2013
Senior Member
PE??51*.*(2004-06) and PE??5A*.* (2007-08) are identical, and contain 2004-06 and 2007-08 all together in the datasets. If you want to analyze 2004-06 vs 2007-08, please select v007 <= 2006, and for 2007-08 select on v007 >= 2007.

Re: Peru 2004 and 2007 [message #8803 is a reply to message #5468] Sun, 20 December 2015 20:14 Go to previous messageGo to next message
gyamada is currently offline  gyamada
Messages: 7
Registered: November 2014
Location: Baltimore

I have a couple of questions about Peru 2004-2008 data (PEIR51FL) in which survey data of multiple years are in one dataset. I am analyzing mothers' BMI calculated from their weight and height data. They corrected anthropometric information in 2005 and 2007-8. My questions are:

1. Can we analyze the data separately for 2007 and 2008, or do we need to analyze in a combined manner? While the final report is available for the period of 2007-8, the method section of the report implies that the country implemented the continuous survey method in order to have estimates every year at certain levels.

2. How can we handle the sampling weights? When I calculated weighted number of observations (see the attached), the sum of weighted numbers of observations per year were different from the sum of observations for each year (although the sum of weighted number of observations across the years 2004-8 was similar to the total number of observations). In other usual surveys, the sampling weight is set so that the sum of sampling weights is similar to the number of unweighted observations.
a. More specifically, when we decide to analyze data of 2007 and 2008 combined, are we supposed to use the sampling weights as they are, or should we re-calibrate/de-normalize sampling weights for each year and combine the data of the two year?
b. Related with the above, when we want to conduct analysis on the entire dataset (e.g. difference of difference analysis), are we supposed to use the sampling weight v005 as given (of course divided by 1,000,000), or are we supposed to re-calibrate the sampling weights for each year?

Thank you,

Re: Peru 2004 and 2007 [message #8894 is a reply to message #8803] Tue, 12 January 2016 03:14 Go to previous message
Messages: 1516
Registered: February 2013
Senior Member
Dear User,
Here is a response from Dr. Shea Rutstein:
Height and weight were only measured in 2005, 2007, and 2008. The original design called for anthropometry every 2 years. However, child malnutrition became a presidential priority with the election of Alan Garcia and there was an expansion of the survey in 2008 to be able to produce departmental-level estimates with greater precision.

The 2004-2008 design called for a different one-fifth subset of the 2000 survey for each continuous survey year, adjusting for changes in cluster size by increasing or decreasing the cluster take and adjusting the final weights for each year for response rates. Thus the weights are combinable over survey years and are not normalized. Normalization does not change the relative weights; however, it does not allow combining years and can't be reversed unless the normalization factor is known.
For 2008, there was a large supplemental sample added from a different sampling frame and weights were calculated to take that into account. Survey years can still be combined with 2008.

[Updated on: Tue, 12 January 2016 11:16]

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