Upananda, here are some of my thoughts about the matter

If your case is acknowledged as qualitative and the findings are opinion- or perception-based, then you do not expect answers to be the same because every individual will have her/his own opinion. If your findings are bio-graphical such as age, income, trarning, education,etc., then you can go to more reliable sources such as birth certificate, income tax returns, certificates or diplomas, instead of their memory recall.

From what I know, it is given that every case is unique hence a case when the situation and the context changed with time is a new case.

The question is, What is the logic of case selection in comparative cases study research? Because of the theoretical issues to be explored and tested, the small-n comparative case study is the appropriate approach to research (Lijphart, 1971; 1975). Keeping in mind the benefits, in terms of internal validity, that experimentation offers and the confidence in causal inferences that it provides, the proposed research strategy optimizes control and effectively isolates the relationships of interest, given the constraints created by our need to observe the phenomenon contextually. One should try to articulate such a method by relying on a logic of case selection that, within the limits inherent in the well-designed small-n comparative case-study (Verba, 1967; Eckstein, 1975; Yin, 1984), allows the researcher to maximize the internal and external validity possible given his/her contextual interests, thus increasing the confidence and generalizability of our causal explanations. Careful attention to the issues of case selection, in case study research, is a critical component of defensibility. The challenge is to determine the research strategy and case selection method most appropriate to the investigators’ theoretical concerns and to their desire to make confident inferences from the findings. How should we do it?

The answer is purposeful sampling of cases for comparison from the universe of cases. Purposeful sampling enables researchers to move away from the indeterminacy that makes generalizations from case studies problematic and in the direction of valid causal explanations of social and political phenomena; for example, the role that research-based knowledge has played in preparing for a probable disaster. Where these concerns pertain, selection of cases in small-n comparative case study research should be guided by some theoretically-driven decision rule. Such a selection process is referred to as theoretical sampling (Mitchell, 1983; Scott, 1987: 158). Cases selected in this manner vary on identified characteristics of theoretical interest. As Fernandez 2005) notes, if researchers hope to explain variation in a dependent variable, the choice of cases must allow for variation in the dependent variable. King and his co-authors (1994, 129) put it bluntly when they ask, “How can we explain variations on a dependent variable if it does not vary?” (p. 129).

I (Goggin, 1986) have identified one common problem that plagues many who design and carry out comparative policy research, the “too few cases/too many variables problem”. One remedy for the too few cases/too many variables problem is to select cases with an eye toward maximizing similarities among cases except for the phenomenon to be explained or maximizing differences among cases except for the phenomenon to be explained (Goggin, 1986:333-34). Przeworski and Tuene (1970:39) label these "most similar" and "most different" systems designs, respectively. The authors describe the differences in these two logics of case selection as follows: “The most similar systems design is based on a belief that a number of theoretically significant differences will be found among similar systems and that these differences can be used in explanation. The alternative design, which seeks maximal heterogeneity in the sample of systems, is based on a belief that in spite of intersystem differentiation, the population will differ with regard to only a limited number of variables or relationships.” The logic of the two designs is identical, with co-variation or the lack thereof, as the instrument for distinguishing relevant from irrelevant variables. It is only the incidence of variability in the dependent variable – some variability in the most similar systems approach and no variability in the most dissimilar systems design – that differentiates these two approaches to case selection in comparative research.

With case study approaches, the researcher(s) will provide the case selection logic (I agree with Malcolm) by explaining why and how the case were selected. Often traditional reliability is less important than "typicality." With typicality, the researcher is arguing that although every case will be different, the case(s) selected are typical of the phenomenon being studied. There are times too when a case is selected for study because it is so atypical. Regardless, your selection process should be transparent.

Thanks, Steven. The example you cite in the last sentence is call "deviant" case analysis (Gerring).

Dear Sir (Malcolm),

Thanks for your time and consideration to reply in a comprehensive manner, which is typical to American researchers (I am a Cornellian). I regret for not respecting your effort immediately and apologize for the delay.

Your explanation on improving reliability is based on case selection to maximize contextual variation. Even though the units of analysis under consideration may similar in both contexts, variables which influence the phenomenon, could not be the same. As a result, one may not able to defend his argument on causal relationship to improve reliability.

 Next, a reasonable response to King (1994) is 'variation of dependable variable' itself could be taken as the unit of analysis.

Upananda