We surveyed researchers in the health and exercise sciences to explore different areas and magnitudes of bias in researchers' decision making. Participants were presented with scenarios (testing a central hypothesis with p = 0.06 or p = 0.04) in a random order and surveyed about what they would do in each scenario. Participants showed significant…

This study investigated the influence of host community on industrial relations practices and policies using Agbara community and Power Holding Company of Nigeria PLC as a case. The study adopted both the qualitative and quantitative methods. A total of 120 samples were drawn from the population using the simple random sampling technique in which…

Purpose: Recent educational research has demonstrated rural-urban gaps in achievement and schooling conditions. Evidence from developing countries is still sparse. This study seeks to report rural-urban disparities in achievement, student, teacher, and school characteristics based on a nationally representative sample of grade four students from…

In 1988, the National Center for Education Statistics (NCES) introduced a proposal to develop a private school data collection that would improve on the sporadic collection of private school data dating back to 1890 and improve on commercially available private school sampling frames. Since 1989, the U.S. Bureau of the Census has conducted the…

A method is proposed for calculating the sample size needed to achieve acceptable statistical power with a given test. The minimally important difference significant (MIDS) criterion for sample size is explained and supported with recommendations for determining sample size. The MIDS criterion is computationally simple and easy to explain. (SLD)

Two basic methods exist for drawing probability samples to be used in telephone surveys: directory sampling (from alphabetical or street directories) and random digit dialing (RDD). RDD includes unlisted numbers, whereas directory sampling includes only listed numbers. The goal of this paper is to estimate the effect of failure to include…

It is shown that using formulae for the estimation of sampling errors based on simple random sampling, when a design actually involves cluster sampling, can lead to serious underestimation of error. Jackknife and balanced repeated replication are recommended as techniques for dealing with this problem. (Author/CTM)