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Adjusting Published Estimates for Exploratory Biases Using the Truncated Normal Distribution

Abstract–Publication bias can occur for many reasons, including the perceived need to present statistically significant results. We propose and compare methods for adjusting a single published estimate for possible publication bias using a truncated normal distribution. We attempt to estimate the mean of the underlying normal sampling distribution using only summary data readily available in most published work, making the results practical for use by a consumer of research. The adjustment methods are investigated via simulation and their results compared in terms of bias, mean squared error, and confidence interval coverage. The methods are also applied to eleven previously published studies. We find the proposed methods improve but do not eliminate biases from the statistical significance filter.

Ketersediaan

Informasi Detail

Judul Seri

THE AMERICAN STATISTICIAN; Vol.75 No.3 August 2021

No. Panggil

-

Penerbit

: .,

Deskripsi Fisik

p. 294-299

Bahasa

English

ISBN/ISSN

-

Klasifikasi

NONE

Tipe Isi

-

Tipe Media

-

Tipe Pembawa

-

Edisi

-

Subjek

REPLICATION
PUBLICATION BIAS
HYPOTHESIS TESTS
STATISTICAL SIGNIFICANCE FILTER

Info Detail Spesifik

-

Pernyataan Tanggungjawab

Travis Loux, Orlando Davy

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