Titre
An Overview of the Fundamentals of Data Management, Analysis, and Interpretation in Quantitative Research.
Type
synthèse (review)
Institution
UNIL/CHUV/Unisanté + institutions partenaires
Périodique
Auteur(s)
Kotronoulas, G.
Auteure/Auteur
Miguel, S.
Auteure/Auteur
Dowling, M.
Auteure/Auteur
Fernández-Ortega, P.
Auteure/Auteur
Colomer-Lahiguera, S.
Auteure/Auteur
Bağçivan, G.
Auteure/Auteur
Pape, E.
Auteure/Auteur
Drury, A.
Auteure/Auteur
Semple, C.
Auteure/Auteur
Dieperink, K.B.
Auteure/Auteur
Papadopoulou, C.
Auteure/Auteur
Liens vers les personnes
Liens vers les unités
ISSN
1878-3449
Statut éditorial
Publié
Date de publication
2023-04
Volume
39
Numéro
2
Première page
151398
Peer-reviewed
Oui
Langue
anglais
Notes
Publication types: Journal Article ; Review
Publication Status: ppublish
Publication Status: ppublish
Résumé
To provide an overview of three consecutive stages involved in the processing of quantitative research data (ie, data management, analysis, and interpretation) with the aid of practical examples to foster enhanced understanding.
Published scientific articles, research textbooks, and expert advice were used.
Typically, a considerable amount of numerical research data is collected that require analysis. On entry into a data set, data must be carefully checked for errors and missing values, and then variables must be defined and coded as part of data management. Quantitative data analysis involves the use of statistics. Descriptive statistics help summarize the variables in a data set to show what is typical for a sample. Measures of central tendency (ie, mean, median, mode), measures of spread (standard deviation), and parameter estimation measures (confidence intervals) may be calculated. Inferential statistics aid in testing hypotheses about whether or not a hypothesized effect, relationship, or difference is likely true. Inferential statistical tests produce a value for probability, the P value. The P value informs about whether an effect, relationship, or difference might exist in reality. Crucially, it must be accompanied by a measure of magnitude (effect size) to help interpret how small or large this effect, relationship, or difference is. Effect sizes provide key information for clinical decision-making in health care.
Developing capacity in the management, analysis, and interpretation of quantitative research data can have a multifaceted impact in enhancing nurses' confidence in understanding, evaluating, and applying quantitative evidence in cancer nursing practice.
Published scientific articles, research textbooks, and expert advice were used.
Typically, a considerable amount of numerical research data is collected that require analysis. On entry into a data set, data must be carefully checked for errors and missing values, and then variables must be defined and coded as part of data management. Quantitative data analysis involves the use of statistics. Descriptive statistics help summarize the variables in a data set to show what is typical for a sample. Measures of central tendency (ie, mean, median, mode), measures of spread (standard deviation), and parameter estimation measures (confidence intervals) may be calculated. Inferential statistics aid in testing hypotheses about whether or not a hypothesized effect, relationship, or difference is likely true. Inferential statistical tests produce a value for probability, the P value. The P value informs about whether an effect, relationship, or difference might exist in reality. Crucially, it must be accompanied by a measure of magnitude (effect size) to help interpret how small or large this effect, relationship, or difference is. Effect sizes provide key information for clinical decision-making in health care.
Developing capacity in the management, analysis, and interpretation of quantitative research data can have a multifaceted impact in enhancing nurses' confidence in understanding, evaluating, and applying quantitative evidence in cancer nursing practice.
PID Serval
serval:BIB_17D27610B7CA
PMID
Open Access
Oui
Date de création
2023-03-13T10:30:50.851Z
Date de création dans IRIS
2025-05-20T15:14:17Z
Fichier(s)![Vignette d'image]()
En cours de chargement...
Nom
1-s2.0-S0749208123000293-main.pdf
Version du manuscrit
published
Licence
https://creativecommons.org/licenses/by/4.0
Taille
1.77 MB
Format
Adobe PDF
PID Serval
serval:BIB_17D27610B7CA.P001
URN
urn:nbn:ch:serval-BIB_17D27610B7CA4
Somme de contrôle
(MD5):2e589f19f7a346e256b555a04a09c3d6