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Related Concept Videos

Correspondence Bias01:17

Correspondence Bias

Correspondence bias, also referred to as the fundamental attribution error, describes the tendency to attribute another person’s behavior to internal characteristics rather than situational influences. This cognitive bias leads individuals to overlook external factors that may be influencing actions, thereby fostering potentially inaccurate assessments of others’ intentions and dispositions.Empirical Evidence for Correspondence BiasResearch has consistently demonstrated the prevalence of...
Surveys02:16

Surveys

Often, psychologists develop surveys as a means of gathering data. Surveys are lists of questions to be answered by research participants, and can be delivered as paper-and-pencil questionnaires, administered electronically, or conducted verbally. Generally, the survey itself can be completed in a short time, and the ease of administering a survey makes it easy to collect data from a large number of people.
Strategies for Assessing and Addressing Confounding01:25

Strategies for Assessing and Addressing Confounding

Confounding is a critical issue in epidemiological studies, often leading to misleading conclusions about associations between exposures and outcomes. It occurs when the relationship between the exposure and the outcome is mixed with the effects of other factors that influence the outcome. Given that, addressing confounding is of high importance for drawing accurate inferences in research.
Confounding can be addressed at both the design phase of a study and through analytical methods after data...
Bias01:22

Bias

Bias refers to any tendency that prevents a question from being considered unprejudiced. In research, bias occurs when one outcome or answer is selected or encouraged over others in sampling or testing. Bias can occur during any research phase, including study design, data collection, analysis, and publication.
In statistics, a sampling bias is created when a sample is collected from a population, and some members of the population are not as likely to be chosen as others (remember, each member...
Bias in Epidemiological Studies01:29

Bias in Epidemiological Studies

Biases can arise at various stages of research, from study design and data collection to analysis and interpretation. Recognizing and addressing these biases is essential to ensure the validity and reliability of epidemiological findings.Broadly speaking, biases in epidemiology fall into three main categories: selection bias, information bias, and confounding. A more detailed description of possible biases is:
Systematic Error: Methodological and Sampling Errors01:15

Systematic Error: Methodological and Sampling Errors

In the case of systematic errors, the sources can be identified, and the errors can be subsequently minimized by addressing these sources. According to the source, systematic errors can be divided into sampling, instrumental, methodological, and personal errors.
Sampling errors originate from improper sampling methods or the wrong sample population. These errors can be minimized by refining the sampling strategy. Defective instruments or faulty calibrations are the sources of instrumental...

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Related Experiment Video

Updated: Jun 26, 2026

Inverse Probability of Treatment Weighting (Propensity Score) using the Military Health System Data Repository and National Death Index
06:55

Inverse Probability of Treatment Weighting (Propensity Score) using the Military Health System Data Repository and National Death Index

Published on: January 8, 2020

Addressing nonresponse bias in postal surveys.

Shannon E MacDonald1, Christine V Newburn-Cook, Donald Schopflocher

  • 1Faculty of Nursing, University of Alberta, Edmonton, Alberta, Canada. smacdon@ualberta.ca

Public Health Nursing (Boston, Mass.)
|January 22, 2009
PubMed
Summary

Postal surveys are simple but require careful handling of nonresponse. Researchers must assess nonresponse bias beyond just response rates to ensure reliable public health nursing data.

Related Experiment Videos

Last Updated: Jun 26, 2026

Inverse Probability of Treatment Weighting (Propensity Score) using the Military Health System Data Repository and National Death Index
06:55

Inverse Probability of Treatment Weighting (Propensity Score) using the Military Health System Data Repository and National Death Index

Published on: January 8, 2020

Area of Science:

  • Nursing Research
  • Public Health
  • Survey Methodology

Background:

  • Postal surveys are a common data collection method in community-based studies.
  • Nonresponse is a significant challenge in postal surveys, potentially impacting data validity.
  • Nurse researchers must carefully consider nonresponse bias, not just response rates.

Purpose of the Study:

  • To discuss the benefits and challenges of postal surveys in public health nursing.
  • To highlight the implications of low response rates and nonresponse bias.
  • To provide guidance on assessing and mitigating nonresponse bias.

Main Methods:

  • Review of literature on postal survey methodology and nonresponse bias.
  • Discussion of potential sources of survey error and their impact.
  • Examination of response-enhancement strategies and their effect on bias.

Main Results:

  • Low response rates can decrease statistical power and increase standard error.
  • Increasing response rates does not automatically reduce nonresponse bias.
  • Strategies to enhance response may inadvertently increase bias if not carefully applied.

Conclusions:

  • Assessing and addressing nonresponse bias is crucial throughout the study design process.
  • Postsurvey data adjustment techniques can help mitigate nonresponse bias.
  • A case study illustrates the importance of considering nonresponse bias in nursing research.