On the Two Different Aspects of the Representative Method: the Method of Stratified Sampling and the Method of Purposive Selection

Neyman, Jerzy

doi:10.1007/978-1-4612-4380-9_12

Cited by 455 publications

(374 citation statements)

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“…A widely used approach to causal reasoning is the potential outcome framework, originally due to Neyman (1934), (see also Rubin, 1990), and developed for observational studies by Rubin (1973). Let us define the timing of a life course event as a binary treatment variable T (T =1 if an individual retires at age a and T = 0 if an individual retires at age a * , with a * > a).…”

Section: Frameworkmentioning

confidence: 99%

Causal Effects of the Timing of Life-course Events: Age at Retirement and Subsequent Health

Barban

Luna

Lundholm

et al. 2017

Sociological Methods & Research

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In this paper we combine the extensive literature on the analysis of life course trajectories as sequences with the literature on causal inference, and propose a new matching approach to investigate the causal effect of the timing of life course events on subsequent outcomes. Our matching approach takes into account pre-event confounders that are both time-independent and time-dependent, as well as life course trajectories. After matching, treated and control individuals can be compared using standard statistical tests or regression models. We apply our approach to the study of the consequences of the age at retirement on subsequent health outcomes, using a unique dataset from Swedish administrative registers. Once selectivity in the timing of retirement is taken into account, effects on hospitalization are small, while early retirement has negative effects on survival. Our approach also allows for heterogeneous treatment effects. We show that the effects of early retirement differ according to pre-retirement income, with higher income individuals tending to benefit from early retirement, while the opposite is true for individuals with lower income.

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Section: Frameworkmentioning

confidence: 99%

Causal Effects of the Timing of Life-course Events: Age at Retirement and Subsequent Health

Barban

Luna

Lundholm

et al. 2017

Sociological Methods & Research

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“…The method proposed in the previous section consists in this case of selecting a stratified sample with the optimal Neyman (1934) allocation, where the variance of the stratum are estimated by means of a previous sample. The notion of optimal inclusion probabilities is thus related to the idea of optimization used by Neyman for the stratified random design.…”

Section: H)mentioning

confidence: 99%

Optimal allocation in balanced sampling

Tillé

Favre

2005

Statistics & Probability Letters

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“…When the cost of the survey per individual is the same in each country, the classic allocation of the sample for a country is proportional to the product of the population size, N i , by the standard deviation of the interest variable S i , for the same country. It is called the Neyman allocation (Neyman, 1934):…”

Section: Sample Size Estimation Principlesmentioning

confidence: 99%

Some statistical aspects of food intake assessment

2002

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Objective: To present the results of the statistical working group of the EFCOSUM project on estimating the minimum sample size for a pan-European dietary survey. Background and methods: Numerous statistical issues are involved when planning a nutritional survey aimed at evaluating various indicators, especially if it will be carried out in different countries. The plenary workshop of the EFCOSUM project has chosen four relevant statistical topics: the sample size estimation for dietary surveys, the number of repeated measurements needed to estimate usual intake for each individual; the statistical presentation of data; and the statistical procedures for estimating the usual intake distribution from a limited number of days of observation. This article deals with the first three topics mentioned. The participants of the EFCOSUM project answered a small questionnaire in order to get agreement on the method of estimating a minimum sample size in the context of a monitoring of dietary indicators. Data on the variability of dietary indicators of interest was also collected, in order to calculate a minimum sample size. Results and conclusion: The main result was that a minimum sample size of 2000 adults in each European country will be needed in order to identify trends in the mean intake of the most relevant foods and nutrients in Europe. This sample size should be higher if trends have to be indentified for socio-demographic subgroups.

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On the Two Different Aspects of the Representative Method: the Method of Stratified Sampling and the Method of Purposive Selection

Cited by 455 publications

References 0 publications

Causal Effects of the Timing of Life-course Events: Age at Retirement and Subsequent Health

Causal Effects of the Timing of Life-course Events: Age at Retirement and Subsequent Health

Optimal allocation in balanced sampling

Some statistical aspects of food intake assessment

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