"Equivalent Sample Size" and "Equivalent Degrees of Freedom" Refinements for Inference Using Survey Weights Under Superpopulation Models

Potthoff, Richard F.; Woodbury, Max A.; Mantón, Kenneth G.

doi:10.2307/2290269

Cited by 56 publications

(63 citation statements)

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“…Sampling variables used to account for the complex design of the NAMCS were not available for all years of interest. We therefore adjusted the sample weights in all analyses according to the method of Potthoff et al 13 which provides estimates of standard errors. Chi-square tests for trends were used to examine the relationship of year with categorical variables and univariate regressions for the relationship of year with continuous variables.…”

Section: Discussionmentioning

confidence: 99%

Trends in Prescribing of Selective Serotonin Reuptake Inhibitors and Other Newer Antidepressant Agents in Adult Primary Care

Pirraglia

Stafford²,

Singer³

2003

Prim. Care Companion CNS Disord.

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Section: Discussionmentioning

confidence: 99%

Trends in Prescribing of Selective Serotonin Reuptake Inhibitors and Other Newer Antidepressant Agents in Adult Primary Care

Pirraglia

Stafford²,

Singer³

2003

Prim. Care Companion CNS Disord.

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“…A Conceptual Framework: The Effective Size of a Geographic Sample A basis for establishing effective sample size for normally distributed georeferenced data is presented in terms of the sampling distribution of a single sample mean; extensions exploiting multiple sample means or the sample correlation coefficient are presented in Appendices A, B, and C. This approach, for which the assumption of a bell-shaped curve is critical, is directly analogous to that reported for time series (e.g., see the R Documentation) and is indirectly analogous to what is reported for survey weights with superpopulation models (Pottchoff, Woodbury, and Manton 1992), whereby applying weights to sample results alters the value of n.…”

Section: Important Considerations When Designing a Sampling Networkmentioning

confidence: 98%

Effective Geographic Sample Size in the Presence of Spatial Autocorrelation

Griffith

2005

Annals of the Association of American Geographers

163

114

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As spatial autocorrelation latent in georeferenced data increases, the amount of duplicate information contained in these data also increases. This property suggests the research question asking what the number of independent observations, say n*, is that is equivalent to the sample size, n, of a data set. This is the notion of effective sample size. Intuitively speaking, when zero spatial autocorrelation prevails, n* = n; when perfect positive spatial autocorrelation prevails in a univariate regional mean problem, n*= 1. Equations are presented for estimating n* based on the sampling distribution of a sample mean or sample correlation coefficient with the goal of obtaining some predetermined level of precision, using the following spatial statistical model specifications: (1) simultaneous autoregressive, (2) geostatistical semivariogram, and (3) spatial filter. These equations are evaluated with simulation experiments and are illustrated with selected empirical examples found in the literature.

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“…asymptotic covariance varies from one parameter to another and therefore it is not possible to mend this method by a simple adjustment of the sample size as in Potthoff, Woodbury, and Manton (1992). The same is true for categorical data analysis.…”

Section: Comparison Among Mplus Mlwin and Hlm/sas Proc Mixedmentioning

confidence: 99%

Sampling Weights in Latent Variable Modeling

Asparouhov¹

2005

Structural Equation Modeling: A Multidisciplinary Journal

492

313

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This article reviews several basic statistical tools needed for modeling data with sampling weights that are implemented in Mplus Version 3. These tools are illustrated in simulation studies for several latent variable models including factor analysis with continuous and categorical indicators, latent class analysis, and growth models. The pseudomaximum likelihood estimation method is reviewed and illustrated with stratified cluster sampling. Additionally, the weighted least squares method for estimating structural equation models with categorical and continuous outcomes implemented in Mplus extended to incorporate sampling weights is also illustrated. The performance of several chi-square tests under unequal probability sampling is evaluated. Simulation studies compare the methods used in several statistical packages such as Mplus, HLM, SAS Proc Mixed, MLwiN, and the weighted sample statistics method used in other software packages.

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"Equivalent Sample Size" and "Equivalent Degrees of Freedom" Refinements for Inference Using Survey Weights Under Superpopulation Models

Cited by 56 publications

References 0 publications

Trends in Prescribing of Selective Serotonin Reuptake Inhibitors and Other Newer Antidepressant Agents in Adult Primary Care

Trends in Prescribing of Selective Serotonin Reuptake Inhibitors and Other Newer Antidepressant Agents in Adult Primary Care

Effective Geographic Sample Size in the Presence of Spatial Autocorrelation

Sampling Weights in Latent Variable Modeling

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