3 edition of Statistical experimentation for household surveys found in the catalog.
Statistical experimentation for household surveys
|Other titles||Household surveys.|
|Statement||Christiaan Grootaert ... [et al.].|
|Series||LSMS working paper,, no. 20|
|Contributions||Grootaert, Christiaan, 1950-|
|LC Classifications||HA4651.5 1976|
|The Physical Object|
|Pagination||66 p. ;|
|Number of Pages||66|
|LC Control Number||82021770|
Populations and Samples Populations In statistics, a population includes all members of a defined group that we are studying for data driven decisions. Sample survey methods As noted above in the section Estimationstatistical inference is the process of using data from a sample to make estimates or test hypotheses about a population. With the aid of decision trees, an optimal decision strategy can be developed. Hensher, John M. The telephone household estimates from the NHIS and the telephone household estimates from the BRFSS were used to correct for nonresponse bias associated with the nontelephone households and then produce a model-based estimate for all counties.
In addition, SRS may also be cumbersome and tedious when sampling from an unusually large target population. Systematic and stratified techniques, discussed below, attempt to overcome this problem by using information about the population to choose a more representative sample. Glantz and Bryan K. While the calibrated approach is a weighted combination of the two, the weights can be poorly estimated, and in simulation studies the calibrated approach can provide worse inference than the model-based approach when the hierarchical model is reasonable.
An example of an SRS would be drawing names from a hat. Surveys and experiments are both techniques used in statistics. Glidden, Stephen C. He prefers to think of everything as models, and, in that sense, the design-based model can be described as a saturated fixed-effects model, in which one does not make strong structural assumptions, so there are no random effects. The third project combined data from two surveys with the goal of providing small-area estimates of cancer risk factors and screening rates to the National Cancer Institute NCI.
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In the case of the estimates that the panel chaired by Kalton was reviewing National Research Council,the updates were coming from the county level, and there were no school district level updates, so the quality of those estimates was not as good as the data that were available for higher levels of geography.
In the example above, using random assignment may create groups that result in 20 blue-eyed people and 5 brown-eyed people in the same group. For example, the distribution of heights among people is better modeled by considering men and women as Statistical experimentation for household surveys book sub-populations.
A random sample is defined as a sample wherein each individual member of the population has a known, non-zero chance of being selected as part of the sample. Altman Find articles by Douglas G. It can generally be assumed that any survey that reports a plus or minus margin of error has been conducted using probability sampling.
Campbell and David A. Montgomery, Elizabeth A. In his third project, he and his team worked hard on obtaining county-level data from a wide variety of sources, not only census data, but also marketing data and data about how active the public health department is.
The goal of the workshop was to begin and to facilitate the much-needed discussion on solutions that range from methodological approaches, such as the use of administrative data, to emphasis on interagency cooperative efforts.
In some cases, Bayes modeling may be a little better because it does a better job with the uncertainty and the variance components. Sample survey methods As noted above in the section Estimationstatistical inference is the process of using data from a sample to make estimates or test hypotheses about a population.
Experiments provide insight into cause-and-effect by demonstrating what outcome occurs when a particular factor is manipulated. Rose and William H. Introduction Scientific progress is driven by developing and testing novel hypotheses. Although in the past the concept of nontelephone households was understood to mean households without a telephone, it is becoming increasingly important to distinguish between households that do not have a telephone at all and households that do not have a landline but do have a cell phone, because the demographic characteristics of these two types of households are different.
Similarly, one can often estimate parameters more accurately if one separates out sub-populations. Stratified sampling, which is discussed below, addresses this weakness of SRS.
Respondents are matched on the covariates and then the missing self-report in the MCBS is imputed, so that the overall self-report rates in the two Statistical experimentation for household surveys book agree.
Dorfman, Richard M. In self-selection bias, those individuals who are highly motivated to respond— typically individuals who have strong opinions— are over-represented, and individuals who are indifferent or apathetic are less likely to respond. Numerous conceptual and methodological differences between the current population household and establishment surveys result in important distinctions in the employment estimates derived from the surveys.
An upper sample size limit of full text papers approximately 50 papers for each of the three taxa and two countries was set prior to the database search, based on pragmatic considerations including the time taken to read each paper in sufficient detail to make a thorough, accurate and reliable assessment.
Quoting George Box, he said that all models are wrong, but some are useful. Unlike in the case of stratified simple random sampling, it is desirable for the clusters to be composed of heterogeneous units.
When data from multiple sources are synthesized, statistical modeling and an imputation framework are particularly useful tools to create the necessary infrastructure. Brocklebank and David A. Sub-Populations A subset of a population is called a sub-population.
For example, researchers might be interested in examining whether cognitive ability as a predictor of Statistical experimentation for household surveys book performance is equally applicable across racial groups. If the experimenter were to assign all of the blue-eyed people to the treatment group and the brown-eyed people to the control group, the results may turn out to be biased.
The list of possible states of nature includes everything that can happen, and the states of nature are defined so Statistical experimentation for household surveys book only one of the states will occur.
Investigating these new ideas using appropriately and robustly designed experiments is fundamental to this process.No. 19 The Conceptual Basis of Measures of Household Welfare and Their Implied Survey Data Requirements No.
20 Statistical Experimentation for Household Surveys: Two Case Studies of Hong Kong No. 21 The Collection of Price Data for the Measurement of Living Standards No.
22 Household Expenditure Surveys: Some Methodological Issues. Statistical Confidence of Results for Household Surveys Size of the Population. Intuitively you would think that the size of the sample required to measure a population would depend on the size of that population – statistically however this is not the case in the majority of household surveys as the population in statistical terms is large enough to be considered infinite – hence a.
Analyzing Food Security Using Household Survey Data: Streamlined Analysis with ADePT Software. c b. was developed to produce food security indicators from food consumption data collected in household surveys.
These indicators, derived at the national and subnational levels, include the consumption of calories and macronutrients, the.Pdf the MAPS key recommendations was the creation of an International Household Survey Network. In doing so, the international community acknowledged the critical role played by sample surveys in supporting the planning, implementation and monitoring of development policies and programs.Oct 08, · A thorough and comprehensive guide to the theoretical, download pdf, and methodological approaches used in survey experiments across disciplines such as political science, health sciences, sociology, economics, psychology, and marketing This book explores and explains the broad range of experimental designs embedded in surveys that use both probability and non-probability samples.
It Author: Paul J. Lavrakas.Statistical Confidence of Results for Household Surveys Size of the Population. Intuitively you ebook think that the size of the sample ebook to measure a population would depend on the size of that population – statistically however this is not the case in the majority of household surveys as the population in statistical terms is large enough to be considered infinite – hence a.