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Related Concept Videos

Surveys02:16

Surveys

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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.
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Data Collection by Survey01:07

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The systematic method of obtaining and analyzing accurate information of a population is called data collection. A survey is a standard method of data collection that involves collecting information from a target human population about their experience, opinion, or knowledge of a product, service, or process. The responses are recorded and interpreted. The most common survey examples are written questionnaires, face-to-face or telephonic conversations, focus groups, and electronic (e-mail or...
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Types of Surveys01:27

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Surveys are essential for marking property boundaries near water bodies. Different types of surveys are defined, each with its own function. Land surveys mark the property boundaries, while route surveys determine the position of properties on nearby highways. Topographic surveys create maps by capturing the three-dimensional features of the land. Hydrographic surveys focus on the shapes of underwater areas and the movement of streams through the properties. Mine surveys determine the relative...
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Convenience Sampling Method00:55

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Sampling is a technique to select a portion (or subset) of the larger population and study that portion (the sample) to gain information about the population. Data are the result of sampling from a population. The sampling method ensures that samples are drawn without bias and accurately represent the population.
Convenience sampling is a non-random method of sample selection; this method selects individuals that are easily accessible and may result in biased data. For example, a marketing...
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The Kaplan-Meier estimator is a non-parametric method used to estimate the survival function from time-to-event data. In medical research, it is frequently employed to measure the proportion of patients surviving for a certain period after treatment. This estimator is fundamental in analyzing time-to-event data, making it indispensable in clinical trials, epidemiological studies, and reliability engineering. By estimating survival probabilities, researchers can evaluate treatment effectiveness,...
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Errors and Mistakes in Surveying01:19

Errors and Mistakes in Surveying

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Errors and mistakes in surveying refer to inaccuracies in measurements and data recording. The errors are deviations from the actual value caused by human sensory limitations, equipment flaws, or environmental effects. These errors are typically unintentional and can result from the inherent imperfections in the instruments used, atmospheric conditions, or the observer’s inability to perceive exact measurements. On the other hand, mistakes are caused by the surveyor's lack of...
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Missing data in surveys: Key concepts, approaches, and applications.

Ardalan Mirzaei1, Stephen R Carter1, Asad E Patanwala1

  • 1School of Pharmacy, Faculty of Medicine and Health, University of Sydney, Australia.

Research in Social & Administrative Pharmacy : RSAP
|March 29, 2021
PubMed
Summary

This paper addresses missing data in survey research, offering guidance on planning, analysis methods like imputation, and reporting. It aims to improve how researchers handle and report incomplete datasets.

Keywords:
Missing dataQuestionnaire designResearch designResearch methodsSurveys

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Area of Science:

  • Survey Methodology
  • Statistical Analysis
  • Research Integrity

Background:

  • A review found low reporting of missing data handling in pharmacy literature.
  • Missing data is a common challenge in survey research.
  • Inconsistent reporting hinders research reproducibility.

Purpose of the Study:

  • To discuss the concept and classification of missing data in surveys.
  • To provide guidance on mitigating missing data occurrence through planning.
  • To detail methods for analyzing and reporting missing data.

Main Methods:

  • Discussion of missing data concepts, classification, and mitigation strategies.
  • Introduction of data analysis techniques including deletion, imputation, and likelihood methods.
  • Presentation of a framework and flowchart for selecting appropriate analysis methods.

Main Results:

  • Guidance provided for planning surveys to minimize missing data.
  • Methods for analyzing data with missing values are introduced.
  • A framework aids in choosing analysis methods based on missing data characteristics.

Conclusions:

  • Effective planning can mitigate missing data occurrence in surveys.
  • Appropriate analysis and reporting of missing data are crucial for research quality.
  • Checklists are provided to guide researchers in reporting missing data practices.