Conceptual Model in a Quantitative Research Project

Conceptual Overview and Discussion

In both quantitative and qualitative deductive case study projects, researchers needs to formulate their expectations of the assumed relationships between the variables that are presented in the conceptual model. In both cases, they will gather data and information in order to discover the extent to which the assumed relationships might be found in reality.

Of course, there are major differences between the detailed elaboration of a conceptual model in a quantitative and a qualitative research project. These differences concern both the process of operationalization, which is the specification of core concepts into indicators, and the selection of the methods of data collection and data analysis.

As Earl Babbie and others have argued, in a quantitative research project the decisions a researcher makes during the process of operationalization will lead to a set of measurable indicators: a set of indicators that can be converted into quantifiable data.

For example, in a practice-oriented research project the researcher aims at clarifying the effects of two indicators Age and Sex of the independent variable Personal Characteristics on two indicators Duration and Perceived Impact on Personal Well-Being of the dependent variable People's Illness. The researcher formulates a set of hypotheses about the relationship between the two sets of indicators. For example, in regard to the relationship between Age and Duration, the researcher expects to find support for the following hypothesis (in the words of Piet Verschuren and Hans Doorewaard):“Older people are ill longer than younger people.”

Please notice that the indicators Age, Sex, and Duration are directly measurable. The indicator Perceived Impact on Personal Well-Being can be measured only indirectly, by means of a transformation into a set of codes.

The researcher selects or develops an appropriate set of data collection instruments. These instruments are designed to gather quantifiable data in the form [Page 208]of numerical scores in order to allow the researcher to carry out a statistical data analysis. One of the most common data collection instruments in quantitative research is a questionnaire. The set of data elicitors in a questionnaire consists of a series of closed questions with standardized answers; they are meant to evoke relevant information from respondents. Some of these questions directly ask the respondents for numerical data.

For example, the numerical data of the indicator Age can be asked directly (“What is your age?”). The same goes for the indicators Duration (“How many days have you been ill?”). Other indicators need to be transformed into codes. Sometimes, the researcher simply ascribes a numerical code to a particular variation. Another frequently used technique is the Likert item. A Likert item is a statement which the respondent is asked to assess. The respondent indicates his or her preferred answer after having selected one out of a set of fixed answer categories. A set of coherent Likert items forms a so-called Likert scale.

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