History of the Uses of Modern Sampling Procedures

Stephan, Frederick F.

doi:10.2307/2280064

Cited by 41 publications

(28 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…7 The discussion here is based on several sources, including Stephan (1948), Eckler (1984), Hansen (1987), and Wakesberg and Goldfield (1997). 8 The ECC universe consisted of households served by a mail carrier (approximately 82% of the US population).…”

Section: B the Evolution Of Unemployment Measures And The 1937 Unempmentioning

confidence: 99%

“…Following the ECC, researchers at the WPA began planning for a national multi-stage sample of the labor force, to be conducted monthly (Stephan, 1948;Hansen, 1987). This survey, called the Monthly Report on the Labor Force (MRLF) was fielded in 64 counties starting in December 1939, and used a 6-month rotating panel (Frankel and Stock, 1939).…”

Section: The Monthly Report On the Labor Forcementioning

confidence: 99%

See 1 more Smart Citation

Origins of the Unemployment Rate: The Lasting Legacy of Measurement without Theory

Card

2011

American Economic Review

View full text Add to dashboard Cite

The modern definition of unemployment emerged in the late 1930s from research conducted at the Works Progress Administration and the Census Bureau. According to this definition, people who are not working but actively searching for work are counted as unemployed. This concept was first used in the Enumerative Check Census, a follow-up sample for the 1937 Census of Unemployment, and continued with the Monthly Report on the Labor Force survey, begun in December 1939 by the Works Progress Administration. A similar definition is now used to measure unemployment around the world.

show abstract

Section: B the Evolution Of Unemployment Measures And The 1937 Unempmentioning

confidence: 99%

Section: The Monthly Report On the Labor Forcementioning

confidence: 99%

Origins of the Unemployment Rate: The Lasting Legacy of Measurement without Theory

Card

2011

American Economic Review

View full text Add to dashboard Cite

show abstract

“…The need for sampling in epidemiological research stems from the nature of several overlapping research designs that are commonly used in the field (17,39,45). For each of these designs, when it is impractical to examine the entire population, statements are made about a targeted group of individuals called the study population, based on observations obtained from a representative portion of the population.…”

Section: Population Sampling In Epidemiologymentioning

confidence: 99%

“…We briefly trace the origins of the two main philosophies of statistical inference in population-based studies. [The reader is referred to several excellent historical reviews of sampling and inference from sample data (31,38,44,45).] We also examine the process of deciding which features to include in creating a statistically appropriate sample of the population.…”

Section: ? Populations Samples and Bridgesmentioning

confidence: 99%

“…some collection of persons or objects about which knowledge was sought) and a sample (i.e. a portion of the population to be observed, thus providing an informational basis for acquiring knowledge about the population).The need for sampling in epidemiological research stems from the nature of several overlapping research designs that are commonly used in the field (17,39,45). For each of these designs, when it is impractical to examine the entire population, statements are made about a targeted group of individuals called the study population, based on observations obtained from a representative portion of the population.…”

mentioning

confidence: 99%

See 1 more Smart Citation

Building Bridges Between Populations and Samples in Epidemiological Studies

Kalsbeek

Heiss

2000

Annu. Rev. Public Health

View full text Add to dashboard Cite

Key Words sample design, statistical inference, sample weights, analysis of data from complex samples s Abstract The increased use of rigorous population-sampling methods and the analysis of data from those samples in cross-sectional surveys, case-control studies, longitudinal-cohort investigations, and other epidemiological research efforts have raised important statistical issues for health analysts. We describe the origin, implications, and some plausible resolutions for several of these issues. Some of the main issues we consider include (a) establishing whom the sample represents; (b) using sample weights; (c) understanding the role of other important features, such as the use of sampling stratification and the selection of clustered groups of population members; and (d ) finding ways to analyze study data with key sampling features in mind. Ultimately, resolution of all of these issues requires that analysts clearly define a reference population and then understand the role of design features in relating sample results to that population. POPULATION SAMPLING IN EPIDEMIOLOGYHistorically, most empirical knowledge has been based on incomplete observation and therefore incomplete samplings of the human experience (46). In each such case there has been a population (i.e. some collection of persons or objects about which knowledge was sought) and a sample (i.e. a portion of the population to be observed, thus providing an informational basis for acquiring knowledge about the population).The need for sampling in epidemiological research stems from the nature of several overlapping research designs that are commonly used in the field (17,39,45). For each of these designs, when it is impractical to examine the entire population, statements are made about a targeted group of individuals called the study population, based on observations obtained from a representative portion of the population.

show abstract

Sampling Error

2003

Introduction to Survey Quality

View full text Add to dashboard Cite

Limit of Liability/Disclaimer of Warranty: While the publisher and author have used their best efforts in preparing this book, they make no representations or warranties with respect to the accuracy or completeness of the contents of this book and specifically disclaim any implied warranties of merchantability or fitness for a particular purpose. No warranty may be created or extended by sales representatives or written sales materials. The advice and strategies contained herein may not be suitable for your situation. You should consult with a professional where appropriate. Neither the publisher nor author shall be liable for any loss of profit or any other commercial damages, including but not limited to special, incidental, consequential, or other damages.

show abstract

History of the Uses of Modern Sampling Procedures

Cited by 41 publications

References 0 publications

Origins of the Unemployment Rate: The Lasting Legacy of Measurement without Theory

Origins of the Unemployment Rate: The Lasting Legacy of Measurement without Theory

Building Bridges Between Populations and Samples in Epidemiological Studies

Sampling Error

Contact Info

Product

Resources

About