Qualitative Studies:Qualitative Studies:Case StudiesCase Studies

IntroductionIntroduction

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

Validity; Quality; Analysis.

Case study methodologyCase 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 methodologyCase 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 methodologyCase 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 biasProblems 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.

GeneralisabilityGeneralisability

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 studiesExploratory 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 studyDesign 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 indicatorsConcepts 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 indicatorsConcepts 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 indicatorsValidity 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 indicatorsValidity of indicators

There are various types of validity:– Face validity;– Criterion validity;– Construct validity;– Internal validity;– External validity.

Face validityFace validity

Face validity involves a subjective evaluation of the indicator using:

Logic; Common sense; Previous reported studies; Jury/Expert opinion.

Criterion validityCriterion 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 validityConstruct 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 validityConstruct validity

In case studies three strategies can be used to increase construct validity:– multiple sources of evidence;– chains of evidence;– informants comments.

Internal validityInternal 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 validityInternal validity

IndependentVariable

DependentVariable

Internal validityInternal validity

IndependentVariable

DependentVariable

Other possibleVariables X

Internal validityInternal 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 validityInternal validity

Selection– observed differences could be the result of

differences within the group. Mortality

– systematic dropout from the study.

Internal validity in case studiesInternal 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.

Internal validity in case studiesInternal validity in case studiesFactor Good Practice

History Multiple case studies

Testing Aviod ‘pc’ questions,Beware of company line,Multiple sources of evidence.

Selection Representitative

Mortality Talk to the same people

External validityExternal 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 validityExternal 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

ReliabilityReliability

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 dataAnalysing 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 dataAnalysing case study data

– conclusions;– outstanding issues:

» further investigation;» other case studies.

Across case studies:– replication;– rigourous thinking.

SummarySummary

A good case study must be: Significant; Complete; Consider all perspectives; Display sufficient evidence; Compelling.