Design of the National Children's Study A Workshop Summary (2013) / Chapter Skim
Currently Skimming:
4 Imputation and Estimation
4 Imputation and Estimation
Pages 45-60
The Chapter Skim interface presents what we've algorithmically identified as the most significant single chunk of text within every page in the chapter.
Select key terms on the right to highlight them within pages of the chapter.
From page 45... ...
for sample weights need to be taken into account in the sample design? Specifically when certain groups 1The study design proposal was described at the beginning of Chapter 3 and was pre sented in Kwan et al.
|
From page 46... ...
Unified Design In responding to the questions above on combining data from different cohorts and imputation, Kalton, O'Muircheartaigh, and Valliant agreed that a unified design with a clearly defined population of inference, as proposed by Kalton, has many advantages over an approach with separate prenatal and birth cohorts. In the unified design outlined by Kalton, the population of inference is defined as all births in a specified enrollment period.
|
From page 47... ...
He noted births may also be picked up at hospitals and birthing centers, but all would be births that occur during the two-year period. This design has the advantages that it is a single integrated design with a clearly defined temporal definition of the population of inference, and benchmark data from birth certificates can be used to support assessment and adjustment.
|
From page 48... ...
If the hospital is considered as a part of the sample design rather than as a separate venture unrelated to the prenatal care providers, then there is a unified, stratified approach to the sample design, and no problem in accumulating data across the two. O'Muircheartaigh stated his default option would be to have equal probabilities of selection for each birth in the defined inferential population.
|
From page 49... ...
Allocation Valliant noted in terms of optimal design, even a unified design approach has allocation issues, including questions about the number of geographic primary sampling units (PSUs) , the number of providers per PSU, and the sample size in each provider.
|
From page 50... ...
He pointed to the somewhat related datasets from the Vanguard sites, with about 4,000 or 5,000 births, and that the NHANES data are health-related with many physical measurements. He also noted the American Hospital Association publishes hospital data.
|
From page 51... ...
He called all of these variables fair game for a research project to determine the most appropriate control totals. Missing Data Kalton noted the problem of missing prenatal data for some births is similar to the attrition problem, except looking at time in the reverse direction.
|
From page 52... ...
He said if it were possible to put together a pseudo-population based on the Vanguard data or NHANES and then divide that population into women with and without the prenatal covariates, for example, a simulation might inform the study about the impact of missing data. Valliant noted the University of Michigan conducts longitudinal surveys, including the Health and Retirement Study and the Panel Survey of Income Dynamics (PSID)
|
From page 53... ...
He agreed almost all longitudinal surveys have most of their non-response in the first wave, and conditional response rates to later waves are quite high, often from 95 to 99 percent. This argues for minimal intrusion at the earliest stage to maximize the initial response rate.
|
From page 54... ...
Kalton said that, in the context of a sample of pregnant women, the hospital sample is designed to provide coverage for women who had no prenatal care or who had prenatal care only from a prenatal care provider that was not included in the provider sampling frame. The number of these women has to be guessed, although sometimes the number can be based on birth certificate data for the hospital from the past year.
|
From page 55... ...
It might be possible to do what household surveys typically do by creating replicates of sample units. If the sample is smaller than expected after recruiting for six months, a replicate of the provider sample could be released.
|
From page 56... ...
Within a twoyear enrollment period, there may be good grounds for including any subsequent births in a selected family with certainty. Then to retain an equal probability sample, it will be important to ensure that prenatal care providers and hospitals do not independently allow the sample to include subsequent pregnancies or births to mothers with a previous birth within the NCS enrollment period.
|
From page 57... ...
would become pregnant. Kalton noted the unified design will collect child data on a schedule of every three months initially and then every six months, and he asked how that would work with the desire to know, almost immediately, when a woman becomes pregnant.
|
From page 58... ...
He said Kalton's point about using statistical methods like weighting and imputation and applying them backward is an interesting idea, but there is a difference between time forward and time backward. Looking at time forward, a study with a strong field operation usually can maintain the sample over time, and the conditional response rate after recruitment is usually very good.
|
From page 59... ...
Kalton responded that, as currently conceived, the data collectors at the hospital have a list of all the prenatal care providers on the sampling frame, and they are instructed to exclude from hospital recruitment all the women who attended any of these providers. The exclusion can be determined either prior to data collection (based on hospital records)
|
Key Terms
This material may be derived from roughly machine-read images, and so is provided only to facilitate research.
More
information on Chapter Skim is available.