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Qualitative Studies: Case Studies. Introduction. In this presentation we will examine the use of case studies in testing research hypotheses: Validity; Quality; Analysis. Case study methodology.

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Introduction
Introduction

  • In this presentation we will examine the use of case studies in testing research hypotheses:

  • Validity;

  • Quality;

  • Analysis.


Case study methodology
Case study methodology

  • Case studies are used as a research tool to test hypotheses in an ex post facto manner ie when the researcher CAN NOT control ANY of the variables under investigation.

  • Case studies are therefore usually concerned with investigating how or why events occurred.


Case study methodology1
Case study methodology

  • Case studies involve examining what has occurred to identify reasons for the occurrence.

  • The lack of control leads to a number of potential problems with case study based research which, if not controlled, can invalidate any conclusions drawn from the research.


Case study methodology2
Case study methodology

  • There are three typical criticisms of the case study methodology:

  • Problems of bias;

  • Lack of generalisability;

  • They are only suitable for explanatory investigations.


Problems of bias
Problems of bias

  • Many researchers are concerned with the apparent lack of rigour involved in case study research (as compared to experimental studies) bought about by investigator bias.

  • Relationships may appear simply because you are looking for them.


Generalisability
Generalisability

  • Because case studies allow no control over any of the variables many question whether conclusions drawn from one specific example can be applied generally.


Exploratory studies
Exploratory studies

  • Many argue that only experimental research can be used to establish causal relationships with case studies being limited in use to the explanatory stage of a research project.

  • This view misses the most important aspect of a case study, its holistic and real-life nature.


Design of a case study
Design of a case study

  • Many of the concerns associated with the use of case studies can be minimised by careful design.

  • Validity is the most important issue to be addressed in the design of a case study methodology.


Concepts and indicators
Concepts and indicators

  • Most research involves measuring concepts (eg intent).

  • Unfortunately concepts are normally abstract and thus not directly observable.

  • Thus indicators (variables) are specified which operationalise the concept.


Concepts and indicators1
Concepts and indicators

  • Unfortunately not all concepts can be easily operationalised and thus the validity of the indicator is drawn into question.

  • One way around this problem is to use multiple indicators each of which are a partial operationalisation of the concept.


Validity of indicators
Validity of indicators

  • The next question is how to evaluate the validity and reliability of the indicators: does it measure what it is supposed to measure.


Validity of indicators1
Validity of indicators

  • There are various types of validity:

    • Face validity;

    • Criterion validity;

    • Construct validity;

    • Internal validity;

    • External validity.


Face validity
Face validity

  • Face validity involves a subjective evaluation of the indicator using:

  • Logic;

  • Common sense;

  • Previous reported studies;

  • Jury/Expert opinion.


Criterion validity
Criterion validity

  • Criterion validity uses a well established indicator to compare the performance of a newly defined indicator.

  • The new indicator behaves in a similar manner to the established one then validity is assumed.


Construct validity
Construct validity

  • Construct validity involves examining one indicator and its relationships to other presumed indicators of the same concept.

  • High correlation between the indicators implies they are valid measures of the concept.

  • Perfect correlation implies redundancy.


Construct validity1
Construct validity

  • In case studies three strategies can be used to increase construct validity:

    • multiple sources of evidence;

    • chains of evidence;

    • informants comments.


Internal validity
Internal validity

  • Internal validity examines the extent to which a research finding (eg A lead to B) is valid.

  • Internal validity involves eliminating all other relationships between other variables (eg C) and B.


Internal validity1
Internal validity

Independent

Variable

Dependent

Variable


Internal validity

Other possible

Variables

X

Independent

Variable

Dependent

Variable


Internal validity2
Internal validity

  • There are numerous factors that can effect internal validity.

  • History/Maturity

    • a long time between observations can cause problems.

  • Testing

    • people behave differently under test conditions.


Internal validity3
Internal validity

  • Selection

    • observed differences could be the result of differences within the group.

  • Mortality

    • systematic dropout from the study.


Internal validity in case studies
Internal validity in case studies

  • The nature of case studies require inferences to be made during data collection.

  • Is the inference correct?

  • Have all possibilities been considered?

  • Is the evidence convergent?

  • The overall quality depends on the quality of the investigator.



External validity
External validity

  • External validity is concerned with the applicability of the research results to other (non examined) populations.

  • Testing

    • attitudes may change as a result of the questioning and the sample thus be unrepresentative.


External validity1
External validity

  • Sample selection

    • self-selecting samples could be biased - include details of those who refused to cooperate.

  • In case studies the use of multiple case studies usually satisfies the requirements for external validity


Reliability
Reliability

  • Reliability is concerned with the reproducibility of measurements.

  • When attitudes are examined how do you know that each respondents ratings are the same?

  • Interview structure, telephone protocols, standard letters, rigour in data collection and pilot studies all help in improving reliability.


Analysing case study data
Analysing case study data

  • Each case study must be reported in detail:

    • the visit;

    • interviews;

    • conversations;

    • facts;

    • evidence in support/rejection of hypotheses


Analysing case study data1
Analysing case study data

  • conclusions;

  • outstanding issues:

    • further investigation;

    • other case studies.

  • Across case studies:

    • replication;

    • rigourous thinking.


  • Summary
    Summary

    • A good case study must be:

    • Significant;

    • Complete;

    • Consider all perspectives;

    • Display sufficient evidence;

    • Compelling.


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