Home » Data » Sampling » Two or Three Sampling Stages
| Two or Three Sampling Stages [message #1710] |
Tue, 01 April 2014 14:13  |
lukassg
Messages: 12
Registered: January 2014
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Hey!
Could someone explain me exactly what is the difference between three-stage and two-stage sampling?
I very well understand the two-stage sampling:
1. I select a certain number of enumeration areas based on a previous census or national survey.
2. I sample a certain number of households from these EAs/clusters.
For the three-stage sampling:
As I understand it, this stage is before the EAs/clusters are selected. So we have even larger areas in the first stage, from which we then select the EAs/clusters in the second stage and the households in the third stage? Why do we have this additional stage in the beginning?
Finally, I am pooling always two different DHS survey for one country to get an over-time estimator of certain effects. I know that I have to adapt the stratification and PSU specifications. Is that enough in the case of a country, e.g. Tanzania, where I pool the years 1999 and 2010, where one year has 3 stages and the other 2 stages? Or does that make it impossible to analyse?
In this context, I also stumble upon probability proportional to size (pps). Can someone explain me this concept as well? :)
Thanks for your help!
Lukas
[Updated on: Tue, 01 April 2014 15:07] Report message to a moderator |
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| Re: Two or Three Sampling Stages [message #1838 is a reply to message #1710] |
Fri, 04 April 2014 08:32  |
Bridgette-DHS
Messages: 3199
Registered: February 2013
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Following is a response to msg_1710, from DHS Senior Sampling Specialist, Ruilin Ren:
1. About the sampling procedure
Most of the DHS surveys use a two-stage cluster sampling procedure and use the latest population census frame. The primary sampling unit (PSU) is the census "Enumeration Area" (EA). After the selection of the EAs, there is a household listing operation. The household listing operation aims to visit all the EAs selected in the first stage and construct a complete list of all residential households in the EA. In the second stage, a certain number of households are selected from the updated list of households. All the selections are random selections.
In the case where a census frame is lacking, like in the Democratic Republic of Congo, there is often a need to select the sample in three stages. In the first stage, a certain number of PSUs (communes) will be selected. After the selection of the PSU, a list of villages (SSU, second sampling unit) in the selected communes will be established. At the second stage, one village will be randomly selected from the list. Then proceeds the household listing in the selected village. In the third stage, the sample households are selected. In summary, when there is no census sampling frame available, the sampling procedure might be multistage, that is, more than two stages.
2. About pooling two surveys
I do not think the sampling procedure matters if pooling different surveys together. But attention should be paid to the sampling weight if the surveys use normalized weights, such as for all the DHS surveys. Since the normalized weight has no unit, it is survey specific. You need to de-normalize the sampling weight first before pooling. De-normalizing means to divide the sampling weight by the overall sampling fraction (number of units selected over the total number of units in the target population), for both household weight and the individual weight, respectively. For example, divide the weight by the ratio of households in the sample for the survey to households in the population, and similarly for women.
3. Probability proportional to size (pps)
This is a sampling procedure in which the chance of a unit being selected in the sample is proportional to the measure of size of the unit. For example, the DHS sampling procedure selects the EAs in the first stage often using PPS sampling, and the measure of size of the EA is usually the number of households in the EA. This means that EAs with a large number of households will have a larger chance to be selected in the sample compared to EAs having a small number of households. This sampling strategy aims to increase the efficiency of the sampling and reduce the sampling errors.
[Updated on: Fri, 04 April 2014 08:34] Report message to a moderator |
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| Re: Two or Three Sampling Stages [message #1839 is a reply to message #1787] |
Fri, 04 April 2014 08:33 |
Bridgette-DHS
Messages: 3199
Registered: February 2013
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Following is a response to msg_1787, from DHS Senior Sampling Specialist, Ruilin Ren:
Stratification means to group similar units into a group (sampling stratum) in the sampling stage, and design and select an independent sample for each sampling stratum. This is aimed at strengthening the representativity of the sample with a given total sample size. Region crossed by urban and rural are frequently used as stratification for DHS surveys. Stratification is for sample selection purposes. There is no restriction on the stratum sample size once it is bigger than 2.
A survey domain is a subpopulation (geographically defined or social-economically, or demographically defined) where most of the survey indicators will be reported for the domain. Regions are usually survey domains in the DHS survey. Survey domain is for reporting purposes. A survey domain can cover many sampling strata, like the regions covering two strata (urban and rural). Since we pay attention to the precision of the indicators calculated/reported, usually there is a minimum sample size requirement for a survey domain. For example, for the DHS surveys, in high fertility countries, DHS requests at least 800 women interviews per domain in order to produce reliable estimates of fertility and childhood mortality at domain level.
[Updated on: Fri, 04 April 2014 08:35] Report message to a moderator |
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| Re: Two or Three Sampling Stages [message #2027 is a reply to message #1838] |
Tue, 15 April 2014 21:10 |
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user-rhs
Messages: 132
Registered: December 2013
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Senior Member |
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Bridgette-DHS wrote on Fri, 04 April 2014 08:32Following is a response to msg_1710, from DHS Senior Sampling Specialist, Ruilin Ren:
[...]
2. About pooling two surveys
I do not think the sampling procedure matters if pooling different surveys together. But attention should be paid to the sampling weight if the surveys use normalized weights, such as for all the DHS surveys. Since the normalized weight has no unit, it is survey specific. You need to de-normalize the sampling weight first before pooling. De-normalizing means to divide the sampling weight by the overall sampling fraction (number of units selected over the total number of units in the target population), for both household weight and the individual weight, respectively. For example, divide the weight by the ratio of households in the sample for the survey to households in the population, and similarly for women.
[...]
Could someone at DHS reconcile the advice given above with the advice from Tom Pullum from an earlier posting (link: http://userforum.dhsprogram.com/index.php?t=msg&th= 136&goto=260&S=608aa561007d1aea931e056a867781f1#msg_ 260)?
Bridgette-DHS wrote on Thu, 04 April 2013 14:28Here is a response from one of our DHS Stata experts Tom Pullum, that should answer your question.
[...]
The weights should be ok. Sometimes surveys from several countries are pooled, and then the weights may need to be changed by a different multiplier for each survey.
[...]
In both cases, the OP asked about pooling different survey waves from the same country (here: Tanzania 1999 and 2010, and in the linked posting Philippines 1998, 2003, and 2008). My understanding is that the weights add up to the sample size for that wave. I'm trying to think of the implications for using the weights as-is. In addition, what is a reliable source of age-sex-specific population size/number of households for the particular survey year needed to de-normalize the weights? Would the PRB have it? World Bank? DHS Program website?
Thanks,
RHS
[Updated on: Tue, 15 April 2014 21:15] Report message to a moderator |
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| Re: Two or Three Sampling Stages [message #2032 is a reply to message #2027] |
Wed, 16 April 2014 11:07 |
Trevor-DHS
Messages: 803
Registered: January 2013
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Both of the messages from Tom and Ruilin are saying essentially the same thing, just in different ways. When combining surveys, you need to adjust the weights so that they are comparable. The easiest way to do that is something like:
new Weight = survey Weight * (Population N / Survey N),
or as Ruilin wrote it "divide the weight by the ratio of households in the sample for the survey to households in the population, and similarly for women":
new Weight = survey Weight / (Survey N / Population N)
The two are equivalent.
The survey Weight and the survey N you have from the dataset. For the population N, you can choose your source of preference. For myself, I usually go to the UN's World Population Prospects: http://esa.un.org/wpp/unpp/panel_indicators.htm . If I am analyzing women, I would pick "Women aged 15-49", Medium variant, and pick the year most appropriate to my analysis for the country.
I hope this helps.
[Updated on: Wed, 16 April 2014 23:50] Report message to a moderator |
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| Re: Two or Three Sampling Stages [message #2033 is a reply to message #2029] |
Wed, 16 April 2014 11:14 |
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user-rhs
Messages: 132
Registered: December 2013
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Senior Member |
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Quote:And as for a reliable source, I looked into it and think the respective censuses are the best approach since the DHS survey are mostly based on them
Ideally, we would use the census figures, but in my experience, the amount and quality of information on the respective Bureau of Statistics/Ministry of Health websites varies by country. Sometimes the age range breakdown is 15-64 instead of 15-49. Also, the census won't be available for all the years that you need. Even in the U.S., the census is done every 10 years with intercensal estimations done annually.
I wonder if DHS can make these figures available for all DHS surveys ever conducted, since the general advice is to de-normalize the sampling weight for pooled analysis. I haven't looked for census HH numbers (haven't had to), but my hunch is that it would be harder to come by than the # of individuals.
One limitation I can think of from relying on the census is that although the most recent census is used as the sampling frame, sometimes it is necessary to make adjustments in the field on the actual # of HH, especially if some time has passed since the census. In stable populations, this is probably OK, but where there is a lot of in and out-migration or population growth/loss, this might be an issue.
[Updated on: Wed, 16 April 2014 11:16] Report message to a moderator |
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