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Data Measurement, Instruments and Sampling.

Data measurement, instrument selection, and sampling are fundamental elements in quantitative research and data collection. Data measurement is the systematic assignment of numeric values or categories to variables to permit measurement with precision and accuracy. Instrument selection involves sele...

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Published in:Journal of Psychiatric & Mental Health Nursing (John Wiley & Sons, Inc.) Vol. 32; no. 3; pp. 680 - 686
Main Authors: Slater, Paul, Hasson, Felicity
Format: tables/charts Journal Article
Published: John Wiley & Sons, Inc. Jun2025
Online Access:View this record in EBSCOhost
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      jtl: Journal of Psychiatric & Mental Health Nursing (John Wiley & Sons, Inc.)
      issn: 13510126
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      dt: Jun2025
      vid: 32
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      pub: John Wiley & Sons, Inc.
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        10.1111/jpm.13142
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        atl: Data Measurement, Instruments and Sampling.
      aug:
        au:
          Slater, Paul
          Hasson, Felicity
        affil: Institute of Nursing and Health Research, Ulster University, Coleraine, UK
      sug:
        subj:
          Data Management
          Research Instruments
          Sample Size Determination
          Data Collection Methods
          Reliability and Validity
          Data Analysis, Statistical
          Scales
          Repeated Measures
          Independent Variable
          Research Measurement
          Visual Analog Scaling
          Semantic Differential Scaling
          Instrument by Type
          Summated Rating Scaling
      ab: Data measurement, instrument selection, and sampling are fundamental elements in quantitative research and data collection. Data measurement is the systematic assignment of numeric values or categories to variables to permit measurement with precision and accuracy. Instrument selection involves selecting the right tool or method to collect data effectively and accurately and ensure the reliability and validity of the data. Sampling is the process of selecting a subset of individuals or items from a larger population to best represent that population, free of bias and generalizable. Understanding these key terms ensures that data collected is valid, reliable, and appropriate for future statistical analysis and interpretation.
      pubtype: Academic Journal
      doctype:
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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