SNAPSHOT OF INDICATORS
Summary of the sample design for PMA2016/Taraba (Nigeria):
PMA2016/Taraba is the first round of PMA2020 data collection in Taraba state and used a two-stage cluster design within the state. Primary sampling units were selected using probability proportional to size procedures within the state. The sample was powered to generate state-level estimates of all women mCPR with less than 3% margin of error. To read more details on our survey methodology including the survey tools, training, data processing and response rates, please scroll to the end of the table below.
Additional detail on sample design, data collection and processing, response rates, and standard errors are available below the indicator tables.
The PMA2016/Taraba Survey in Detail
Round 1 Sample Design
For this first round of PMA2020 data collection in Taraba, Nigeria (PMA2016/Taraba), the project used a two-stage cluster design within the state and drew a sample of 20 enumeration areas (EAs) from the National Population Commission master sampling frame to achieve a representative sample of Taraba State. The master frame of enumeration areas (EAs) was based on the 2006 Nigerian population census. Census EAs in Nigeria are on average 47 households in size. In order to obtain an EA of approximately 200 households, a cluster of EAs was constructed – hereinafter referred to as EA cluster. An index enumeration area, along with a list of contiguous EAs and associated sampling probabilities, were provided by the National Population Commission (NPopC). EAs were combined into EA clusters - primary sampling units in Nigeria - and sampling probabilities were adjusted.
In each selected EA cluster households and private health facilities were listed and mapped. Field supervisors randomly selected 35 households from the household listing using a random number generation phone application. A household roster was completed and all eligible women age 15-49 in selected households were approached and asked to provide informed consent to participate in the study.
For the SDP survey, up to three private SDPs, including pharmacies, within each sampled EA cluster boundary were randomly selected from the listing. In addition, three public health SDPs—a health post, a health center, and a district hospital designated to serve the EA population—were selected.
Training, Data Collection and Processing
Throughout the training, resident enumerators and supervisors were evaluated based on their performance on phone-based assessments. The RE training was conducted in Hausa and English, whereas some small group review sessions were conducted in other local languages.
Supervisors received additional training prior to and after the RE training to further strengthen their supervision skills, including instruction on conducting re-interviews, carrying out random spot checks, and dealing with the local/community leaders and engaging the communities.
Data Collection and Processing
The ODK application enabled REs and supervisors to collect and transfer survey data to a central ODK Aggregate cloud server. This instantaneous aggregation of data also allowed for concurrent data processing and course corrections while PMA2020 was still active in the field. Throughout data collection, central staff at CRERD in Nigeria, and the data manager at the Gates Institute at Johns Hopkins in Baltimore, Maryland routinely monitored the incoming data and notified field staff of any potential errors, missing data or problems found with form submissions on the central server. The use of mobile phones combined data collection and data entry into one step; therefore, data entry was completed when the last interview form was uploaded at the end of data collection in June.
Once all data were on the server, data analysts cleaned and de-identified the data, applied survey weights, and prepared the final dataset for analysis using Stata. The findings were shared with government and community stakeholders at a dissemination event in October 13, 2016.
|Household response rate* (%)||100.0||99.5||99.6|
|Interviews with women age 15-49|
|Number of eligible women**||134||732||866|
|Number of eligible women interviewed||132||718||850|
|Eligible women response rate† (%)||98.5||98.1||98,2|
Sample Error Estimates
|Variable||Value[R]||Standard Error||Confidence Interval|
|All women age 15-49|
|Currently using a modern method||0.099||0.028||0.041||0.158|
|Currently using a traditional method||0.029||0.013||0.002||0.056|
|Currently using any contraceptive method||0.129||0.038||0.050||0.208|
|Currently using injectables||0.034||0.009||0.014||0.053|
|Currently using male condoms||0.032||0.015||0.001||0.063|
|Currently using implants||0.004||0.003||-0.003||0.010|
|Chose method by self or jointly in past 12 months||0.861||0.042||0.772||0.949|
|Paid fees for family planning services in past 12 months||0.515||0.111||0.279||0.751|
|Informed by provider about other methods||0.322||0.047||0.221||0.423|
|Informed by provider about side effects||0.369||0.040||0.284||0.455|
|Satisfied with provider: Would return and refer friend/relative to provider||0.759||0.079||0.598||0.920|
|Visited by health worker who talked about family planning in past 12 months||0.096||0.021||0.052||0.139|
|Women in union age 15-49|
|Currently using a modern method||0.096||0.031||0.030||0.162|
|Currently using a traditional method||0.029||0.016||-0.005||0.064|
|Currently using any contraceptive modern method||0.125||0.040||0.042||0.208|
|Currently using injectables||0.044||0.014||0.015||0.074|
|Currently using male condoms||0.010||0.006||-0.001||0.022|
|Currently using implants||0.006||0.005||-0.004||0.015|
|Chose method by self or jointly in past 12 months||0.868||0.044||0.775||0.960|
|Paid fees for family planning services in past 12 months||0.520||0.110||0.286||0.754|
|Informed by provider about other methods||0.374||0.078||0.207||0.541|
|Informed by provider about side effects||0.443||0.064||0.307||0.579|
|Satisfied with provider: Would return and refer friend/relative to provider||0.705||0.101||0.490||0.920|
|Visited by health worker who talked about family planning in past 12 months||0.109||0.022||0.063||0.154|