Reliability of estimates with alternative cluster sizes in the Health Interview Survey evaluation of loss in precision due to clustering of households by Joseph Waksberg

Cover of: Reliability of estimates with alternative cluster sizes in the Health Interview Survey | Joseph Waksberg

Published by U.S. National Center for Health Statistics; [for sale by the Supt. of Docs., U.S. Govt. Print. Off., Washington] in Rockville, Md .

Written in English

Read online

Subjects:

  • Health surveys -- Statistical methods.,
  • Sampling (Statistics)

Edition Notes

Book details

Statement[by Joseph Waksberg, Robert H. Hanson, and Curtis A. Jacobs]
SeriesNational Center for Health Statistics. Vital and health statistics. Series 2: Data evaluation and methods research,, no. 52, DHEW publication, no. (HSM) 73-1326, Vital and health statistics., no. 52., DHEW publication ;, no. (HSM) 73-1326.
ContributionsHanson, Robert Harold, 1918- joint author., Jacobs, Curtis A., joint author., United States. Bureau of the Census.
Classifications
LC ClassificationsRA409 .U45 no. 52
The Physical Object
Paginationv, 17 p.
Number of Pages17
ID Numbers
Open LibraryOL5389060M
LC Control Number72600131

Download Reliability of estimates with alternative cluster sizes in the Health Interview Survey

Reliability of Estimates With Alternative Cluster Sizes in the Health InterviewSurvey Evaluation of loss in precision due to clustering of households.

DHEW Publication No. (HSM), U.S. DEPARTMENT OF HEALTH, EDUCATION, AND WELFARE Public Health Service Health Services and Mental Health Administration. Vital Health Stat 2. Apr;(52) Reliability of Estimates With Alternative Cluster Sizes in the Health InterviewSurvey. Waksberg J, Hanson RH, Jacobs CA.

The practice of grouping the elements of the universe of study into clusters and sampling the clusters is a common feature of sample by: 1. Reliability of estimates with alternative cluster sizes in the Health Interview Survey: evaluation of loss in precision due to clustering of households.

[Joseph Waksberg; Robert Harold Hanson; Curtis A Jacobs; United States. Title(s): Reliability of estimates with alternative cluster sizes in the Health Interview Survey; evaluation of loss in precision due to clustering of households.

Country of Publication: United States Publisher: Rockville, Md. Reliability of estimates with alternative cluster sizes in the Health Interview Survey.

Health Surveys--United States, Sampling Studies, RAU45 no. 52 Author: National Center for Health Statistics (U.S.). Vital and Health Statistics Series Reports from the National Health Interview Survey. Related Pages.

Reliability of Estimates With Alternative Cluster Sizes in the Health Interview Survey. Waksberg, J., Hanson, R. Reliability of estimates with alternative cluster sizes in the health interview survey: evaluation of loss in precision due tu clustering of households Report of operations for the year Report to the Congress.

Healthstyles and NHIS, BRFSS comparisons - Regarding the Healthstyles8 survey, some of the items do overlap with those in the National Health Interview Survey and the Behavioral Risk Factor Surveillance System. The Office of Communication=s File Size: 22KB. so in cluster sampling, A.

s an example, for a size of clus if =the deff = 1+()* = suggesting that the actual variance is times above what it would have been wit. ariance from SRS with same sample size. However, if the size of cluster is large, say m=, deff=1+()*=.

When ρ =deff= Size: KB. A good maximum sample size is usually 10% as long as it does not exceed A good maximum sample size is usually around 10% of the population, as long as this does not exceed For example, in a population of10% would be a.

In cluster sampling, the parent population is broken into mutually exclusive and exhaustive sub-groups and a simple random sample is selected from each subgroup. Cluster samples are most statistically efficient when the clusters are internally homogeneous.

I have created an Excel spreadsheet to automatically calculate split-half reliability with Spearman-Brown adjustment, KR, KR, and Cronbach's alpha. The reliability estimates are incorrect if you have missing data.

KRl and KR only work when data are entered as 0 and 1. Split-hal Author: Del Siegle. Evaluating survey questions. Validity and reliability. Researchers evaluate survey questions with respect to: (1) validity and (2) reliability.

In order to think about validity and reliability, it helps to compare the job of a survey researcher to the job of a doctor. Say a patient comes to the doctor with some aches and pains.

The term reliability in this context refers to the precision of the measurement (i.e. small variability in the observations that would be made on the same subject on different occasions) but is not concerned with the potential existence of bias.

External reliability: results from test–retest in the WHS Fig. 1 reports the ICCs for the test–retest responses for total household expenditure and expenditures on educa-tion, food and health. Each vertical bar depicts a country, and the range shows the 95% confidence intervals around the mean estimate of the ICC.

For most countries, the. Reliability and validity estimates for the Healthy Home Survey were varied, but generally high (– and – respectively), with lower scores noted for perishable foods and policy by: Health and Nutrition Survey, the National Survey on Family and Economic Conditions, and the National Health Interview Survey.

These survey datasets provide the benefits of nationally representative samples, which often are difficult to obtain directly. When national survey datasets contain many health-related variables,Cited by: 3. The estimation of measurement reliability is not straightforward, and there is a virtual absence.

of discussion in the survey methods literature of the problems of designing measurement strategies in such a way that useful estimates of reliability can be obtained.3 Two general design strategies haveCited by: measured, the estimates required, the reliability and validity needed to ensure the usefulness of the estimates, and any resource limitations that may exist pertaining to the conduct of the survey (Levy & Lemeshow,p.

Small-Area Estimation. FINDING THE BOUNDARIES: WHEN DO DIRECT SURVEY ESTIMATES MEET SMALL-AREA NEEDS. This session focused on the topic of producing estimates in situations in which only a small amount of information is available or there are other limitations, such as physical, temporal, or conceptual boundaries that make direct estimation.

We estimate test-retest reliability when we administer the same test to the same sample on two different occasions. This approach assumes that there is no substantial change in the construct being measured between the two occasions. The amount of time allowed between measures is critical.

We know that if we measure the same thing twice that the. A Guide to Sampling for Community Health Assessments and Other Projects randomization), and then we’ll move into some issues more specific to community health assessment (sample size issues and oversampling).

Finally, we’ll end with weighting, an important but often under-used statistical technique that might be helpful during your Size: KB. Survey research involves studying people's characteristics, behaviors, and intentions by asking them to answer questions.

One survey method is through personal interviews, in which interviewers meet respondents face-to-face and question them. ____ ____ are less costly, but are inadvisable if the interview is long or if the questions are sensitive.

Also, sample size calculations for special types of RCTs, like cluster-randomized trials, in which health interventions are allocated randomly to intact clusters, communities, health centres or practices rather than to individual subjects, need an alternative approach.

The same holds true for trials with a crossover design, because these Cited by: Sample size determination in health studies' a practical manual 1 Sampling studies surveys I. Lemeshow, S to Lemeshow, S. et aI., Adequacy of sample size in health studies (Chichester, John Wiley, ; published on behalf of the World Health Organization) cluster sampling strategy the design effect might be estimated as 2.

This. Survey Methods & Sampling Techniques Geert Molenberghs Interuniversity Institute for Biostatistics and statistical Bioinformatics (I-BioStat) Katholieke Universiteit Leuven & Universiteit Hasselt, Belgium [email protected] Master in Quantitative Methods, Katholieke Universiteit BrusselFile Size: 2MB.

estimates of substance use and mental health issues from the National Survey on Drug Use and Health (NSDUH), an annual survey of the civilian, noninstitutionalized population of the United States aged 12 years old or older.

NSDUH is the primary source of statistical information. The ‘design effect’ (DE) can be used to estimate the extent to which the sample size should be inflated to accommodate for the homogeneity in the clustered data: DE = 1+(n-1)ρ n = average cluster size ρ = ICC for the desired outcome.

The DE can then be used to calculate the ‘effective sample size’. Questionnaire Design and Surveys Sampling.

The contents of this site are aimed at students who need to perform basic statistical analyses on data from sample surveys, especially those in marketing science.

Students are expected to have a basic knowledge of statistics, such as descriptive statistics and the concept of hypothesis testing. • Analysis of secondary data, where “secondary data can include any – Application of weights and alternative methods of variance estimation • Common approach when analyzing large secondary datasets due to complexity of sampling design be rounded and/or estimates based on small sample sizes to be suppressedFile Size: 1MB.

The particular sample used for each survey included in this report is one of a large number of samples of the same size that could have been selected using the same design. For the ASM, we estimate sampling variances using the Poisson variance estimator, rather than the method of random groups.

When there is no bias in a sample, increasing the sample size tends to increase the precision and reliability of the estimate. When a sample is biased, it may be impossible to decipher helpful information from the data, even if the sample is very large.

Checkpoint The reliability of self-report data is an Achilles’ heel of survey research. For example, opinion polls indicated that more than 40 percent of Americans attend church every week. However, by examining church attendance records, Hadaway and Marlar () concluded that the actual attendance was fewer than 22 percent.

Survey Methods and Reliability of Data INTRODUCTION This appendix describes the data sources, sample design, and estimation procedures used to develop quarterly estimates of expenditures for the improvement and repairs to residential properties.

This description refers to the revised survey methods effective with fourth-quarter data. Parallel forms reliability relates to a measure that is obtained by conducting assessment of the same phenomena with the participation of the same sample group via more than one assessment method.

Example: The levels of employee satisfaction of ABC Company may be assessed with questionnaires, in-depth interviews and focus groups and results can be compared. Special topics (design issues for pre-post survey sampling for program evaluation and longitudinal study design, WHO/EPI cluster sampling, Lot Qu ality Assurance Sampling[LQAS], sample size estimation for program evaluation)File Size: KB.

A 'read' is counted each time someone views a publication summary (such as the title, abstract, and list of authors), clicks on a figure, or views or downloads the full-text.

Concept of Data Author: Syed Muhammad Sajjad Kabir. Snowball sampling (also known as chain-referral sampling) is a non-probability (non-random) sampling method used when characteristics to be possessed by samples are rare and difficult to find. For example, if you are studying the level of customer satisfaction among elite Nirvana Bali Golf Club in Bali, you will find it increasingly difficult to find primary data sources unless a.

Design: Data from the National Health Interview Survey (NHIS), a cross-sectional, household survey representative of the U.S. civilian population, were used, which included the Complementary. Summary View help for Summary. The National Social Life, Health and Aging Project (NSHAP) is the first population-based study of health and social factors on a national scale, aiming to understand the well-being of older, community-dwelling Americans by examining the interactions among physical health, illness, medication use, cognitive function, emotional health, sensory function, health.

Reliability and validity of measurements are important for the interpretation and generalisation of research findings. Valid, reliable and comparable measures of health status of individuals are critical components of the evidence base for health policy.

The need for sound information is especially urgent in the case of emerging diseases and other acute health Cited by: 9.The survey is an appropriate means of gathering information under three conditions: when the goals of the research call for quantitative and qualitative data, when the information sought is specific and familiar to the respondents andFile Size: KB.Comparison of the reliability of nationally representative estimates from the full () and half () sample National Hospital consequences this decision had on estimates from the survey.

Overview of the National Hospital Discharge Survey (NHDS) cluster design. Inthe survey was redesigned and a new sample of hospitals was.

1715 views Sunday, November 22, 2020