Standard

Good relations : the use of a relational database for large-scale data analysis. / Moseley, L G; Mead, D M.

In: Journal of Advanced Nursing, Vol. 18, No. 11, 11.1993, p. 1795-805.

Research output: Contribution to journalArticle

Harvard

Moseley, LG & Mead, DM 1993, 'Good relations: the use of a relational database for large-scale data analysis', Journal of Advanced Nursing, vol. 18, no. 11, pp. 1795-805. https://doi.org/10.1046/j.1365-2648.1993.18111795.x

APA

Moseley, L. G., & Mead, D. M. (1993). Good relations: the use of a relational database for large-scale data analysis. Journal of Advanced Nursing, 18(11), 1795-805. https://doi.org/10.1046/j.1365-2648.1993.18111795.x

Vancouver

Author

Moseley, L G ; Mead, D M. / Good relations : the use of a relational database for large-scale data analysis. In: Journal of Advanced Nursing. 1993 ; Vol. 18, No. 11. pp. 1795-805.

BibTeX

@article{f19723dda53646acbeb37454b8a43372,
title = "Good relations: the use of a relational database for large-scale data analysis",
abstract = "This paper reports our experience of analysing what may well be one of the largest datasets gathered on nursing practice in the United Kingdom. The study produced both quantitative and qualitative data and a method had to be devised both for analysing each form of data and for relating the two. An inexpensive relational database was chosen for the purpose, and experience of using it is reported. Detailed examples are given. We look at the strengths and weaknesses of such a tool, and in general it received a positive evaluation. For many nursing research projects, it offers some advantages over a conventional statistical package, especially in the following areas: offering ease of use, and hence control of the data, by the domain (nursing) specialist; facilitating the analysis of free-text data; allowing the linking of free-text and structured questionnaire data; permitting the testing of conjectures which arise during analysis; handling varying amounts of data per case; providing non-redundant storage of data; permitting the association of machine-readable codes and human-readable labels; and encouraging an exploratory rather than merely analytical approach.",
keywords = "Data Interpretation, Statistical, Databases, Factual, Factor Analysis, Statistical, Humans, Nursing, Nursing Research, Nursing, Team, Primary Nursing, Software, Journal Article",
author = "Moseley, {L G} and Mead, {D M}",
year = "1993",
month = nov,
doi = "10.1046/j.1365-2648.1993.18111795.x",
language = "English",
volume = "18",
pages = "1795--805",
journal = "Journal of Advanced Nursing",
issn = "0309-2402",
publisher = "Wiley",
number = "11",

}

RIS

TY - JOUR

T1 - Good relations

T2 - the use of a relational database for large-scale data analysis

AU - Moseley, L G

AU - Mead, D M

PY - 1993/11

Y1 - 1993/11

N2 - This paper reports our experience of analysing what may well be one of the largest datasets gathered on nursing practice in the United Kingdom. The study produced both quantitative and qualitative data and a method had to be devised both for analysing each form of data and for relating the two. An inexpensive relational database was chosen for the purpose, and experience of using it is reported. Detailed examples are given. We look at the strengths and weaknesses of such a tool, and in general it received a positive evaluation. For many nursing research projects, it offers some advantages over a conventional statistical package, especially in the following areas: offering ease of use, and hence control of the data, by the domain (nursing) specialist; facilitating the analysis of free-text data; allowing the linking of free-text and structured questionnaire data; permitting the testing of conjectures which arise during analysis; handling varying amounts of data per case; providing non-redundant storage of data; permitting the association of machine-readable codes and human-readable labels; and encouraging an exploratory rather than merely analytical approach.

AB - This paper reports our experience of analysing what may well be one of the largest datasets gathered on nursing practice in the United Kingdom. The study produced both quantitative and qualitative data and a method had to be devised both for analysing each form of data and for relating the two. An inexpensive relational database was chosen for the purpose, and experience of using it is reported. Detailed examples are given. We look at the strengths and weaknesses of such a tool, and in general it received a positive evaluation. For many nursing research projects, it offers some advantages over a conventional statistical package, especially in the following areas: offering ease of use, and hence control of the data, by the domain (nursing) specialist; facilitating the analysis of free-text data; allowing the linking of free-text and structured questionnaire data; permitting the testing of conjectures which arise during analysis; handling varying amounts of data per case; providing non-redundant storage of data; permitting the association of machine-readable codes and human-readable labels; and encouraging an exploratory rather than merely analytical approach.

KW - Data Interpretation, Statistical

KW - Databases, Factual

KW - Factor Analysis, Statistical

KW - Humans

KW - Nursing

KW - Nursing Research

KW - Nursing, Team

KW - Primary Nursing

KW - Software

KW - Journal Article

U2 - 10.1046/j.1365-2648.1993.18111795.x

DO - 10.1046/j.1365-2648.1993.18111795.x

M3 - Article

C2 - 8288826

VL - 18

SP - 1795

EP - 1805

JO - Journal of Advanced Nursing

JF - Journal of Advanced Nursing

SN - 0309-2402

IS - 11

ER -

ID: 1221264