Quantitative Data Management

Quantitative Data Management

Quantitative Data Management Chapter 18

Nursing Research

Florida National University





Commencing Quantitative Data Management

As soon as you begin collecting data. It is time to consider what to do with it as it comes in. You could just allow the data to accumulate and deal with it later. But there are several reasons not to do this. The first reason is probably obvious: if you do not begin to manage the data right away, you will have a huge job awaiting you later.


Tappen, R. M. (2015). Advanced Nursing Research: From Theory to Practice (2nd ed.). Jones & Bartlett Learning.





Brief Review of Quantitative Research

Before we go further, let us make sure that we understand quantitative research. What is Quantitative Research/Methodology?

Quantitative methodology is the dominant research framework in the social sciences. It refers to a set of strategies, techniques and assumptions used to study psychological, social and economic processes through the exploration of numeric patterns.

Quantitative research gathers a range of numeric data. Some of the numeric data is intrinsically quantitative (i.e., personal income), while in other cases the numeric structure is imposed (i.e., ‘On a scale from 1 to 10, how depressed did you feel last week?’).

The collection of quantitative information allows researchers to conduct simple to extremely sophisticated statistical analyses that aggregate the data (i.e., averages, percentages), show relationships among the data (i.e., ‘Students with lower grade point averages tend to score lower on a depression scale’) or compare across aggregated data (i.e., the USA has a higher gross domestic product than Spain).

Quantitative research includes methodologies such as questionnaires, structured observations or experiments and stands in contrast to qualitative research.

Qualitative research involves the collection and analysis of narratives and/or open-ended observations through methodologies such as interviews, focus groups or ethnographies.


Coghlan, D., Brydon-Miller, M. (2014). The SAGE encyclopedia of action research (Vols. 1-2). London, : SAGE Publications Ltd doi: 10.4135/9781446294406





Watch For The Following Issues As They Relate To Quantitative Data Management

Signatures on consents are not witnessed; copies of the consent have not been given to every participant.

Duplicate identification (ID) numbers have been inadvertently assigned to participants. (This can happen, for example, if you use the last four digits of the Social Security number, which has been a common but not recommended practice.)

Rating scales are scored incorrectly. This is most likely to happen with scales that have complicated scoring rules.

Scale scores are not correctly totaled (mathematical errors).

The wrong version of a test was used—the short form of the CES-D (a depression scale) or STAI (an anxiety scale), for example, instead of the long form.

A page is missing from the test packet, so items are missing.

An important variable such as age or gender has been left out by mistake.

Items are missed or left blank.

Responses to open-ended questions are difficult to read or too abbreviated to be useful.







Watch For The Following Issues As They Relate To Quantitative Data Management

Most of these errors are more likely to occur if you have someone else collecting or entering data for you or if participants are completing the forms themselves either on paper or electronically.

Failure to correct these problems as quickly as possible may lead to serious problems later, particularly when you try to analyze the results of the study.

A third reason to begin data management as soon as data collection begins is to make it possible to conduct preliminary analyses of the results at several points during the study. If the study is funded, the funder may require interim reports including some preliminary results. Also, if your study involves an intervention, the preliminary analysis may indicate some concerns about the intervention that would otherwise not be known until the end of the study. A series of periodic preliminary or interim analyses are essential if the intervention requires a data and safety monitoring plan (Cook & DeMets, 2008).