Qualitative research usually produces large amounts of textual data in the form of transcripts and field notes. In recent years, there has been an increase in number of qualitative studies been carried out by health professionals. However, when we want to broaden or deepen our understanding of how things came to be the way they are in our social world, qualitative research has no substitute 1. Quantitative research tells us how often or how many behave in a certain way. CAQDAS are basically data management packages, which support the researcher during analysis.
How to classify attribute and value data in nvivo 12 software#
In other words, researchers must equally know that no software can analyse qualitative data. The key message is that unlike statistical software, the main function of CAQDAS is not to analyse data but rather to aid the analysis process, which the researcher must always remain in control of.
In this paper, the author reflects on his experience of interacting with one of the popular CAQDAS (NVivo) in order to provide evidence-based implications of using the software. While the issue of mastering CAQDAS has received ample attention, little has been done to address the misconceptions associated with CAQDAS. This may be due to the difficulties that one has to go through to master the software and the misconceptions that are associated with using CAQDAS. Although the CAQDAS has been there for decades, very few qualitative health researchers report using it. However, Computer Assisted Qualitative Data Analysis Software (CAQDAS) are increasingly being developed. The weights of the football players on the teams that play in the NFL this year.For a long time, electronic data analysis has been associated with quantitative methods.The amount of money a person earns per week working at a fast-food restaurant.The number of touchdowns a quarterback scored each year in his college football career.The number of hours during a week that children ages 12 to 15 reported that they watched television.The classification of variables can be summarized as follows:Ĭlassify each variable as a discrete or continuous variable. They often include fractions and decimals. Temperature, for example, is a continuous variable, since the variable can assume an infinite number of values between any two given temperatures.Ĭontinuous variables can assume an infinite number of values between any two specific values.
Discrete variables can be assigned values such as 0, 1, 2, 3 and are said to be countable. Examples of discrete variables are the number of children in a family, the number of students in a classroom, and the number of calls received by a call center each day for a month.ĭiscrete variables assume values that can be counted.Ĭontinuous variables, by comparison, can assume an infinite number of values in an interval between any two specific values. Quantitative variables can be further classified into two groups: discrete and continuous. Other examples of quantitative variables are heights, weights, and body temperatures.
Quantitative variables are variables that can be counted or measured.įor example, the variable age is numerical, and people can be ranked in order according to the value of their ages. Other examples of qualitative variables are religious preference and geographic locations. Qualitative variables are variables that have distinct categories according to some characteristic or attribute.įor example, if subjects are classified according to gender (male or female), then the variable gender is qualitative. Variables can be classified as qualitative or quantitative. Today i will teach you about the types of variables and types of data
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