Qualitative data is extremely varied in nature. It includes virtually any information that can be captured that is not numerical in nature. Here are some of the major categories or types: 
 
In-Depth Interviews 
In-Depth Interviews include both individual interviews (e.g., one-on-one) as well as "group" interviews (including focus groups). The data can be recorded in a wide variety of ways including stenography, audio recording, video recording or written notes. In depth interviews differ from direct observation primarily in the nature of the interaction. In interviews it is assumed that there is a questioner and one or more interviewees. The purpose of the interview is to probe the ideas of the interviewees about the phenomenon of interest. 
 
Direct Observation 
Direct observation is meant very broadly here. It differs from interviewing in that the observer does not actively query the respondent. It can include everything from field research where one lives in another context or culture for a period of time to photographs that illustrate some aspect of the phenomenon. The data can be recorded in many of the same ways as interviews (stenography, audio, video) and through pictures, photos or drawings (e.g., those courtroom drawings of witnesses are a form of direct observation). 
 
Written Documents 
Usually this refers to existing documents (as opposed transcripts of interviews conducted for the research). It can include newspapers, magazines, books, websites, memos, transcripts of conversations, annual reports, and so on. Usually written documents are analyzed with some form of content analysis. 
 
sumber : http://www.socialresearchmethods.net/kb/qualdata.php

Qualitative Data Analysis

During the past two decades, a set of systematic comparative case analysis techniques has been developing at a steady pace. During the last few years especially, the main initial technique, qualitative comparative analysis (QCA), has been complemented by other related methods and techniques. The purpose of this article is to critically assess some main recent developments in this field. QCA and connected methods can be considered at two levels: as a research strategy and as a set of concrete techniques. The author first argues that such a strategy displays some decisive advantages in social science research, especially in small-and intermediate-N research designs. Second, QCA as well as three other related techniques, namely multi-value QCA (MVQCA), fuzzy sets and MSDO/MDSO, are presented in brief, and some current debates with regard to these techniques are also summarized. In the third section, the article surveys recent contributions and ongoing efforts that have provided some advances in the applicati...

Qualitative Comparative Analysis (QCA) and Related Systematic Comparative Methods Recent Advances and Remaining Challenges for Social Science Research

Systematic reviews that address policy and practice questions in relation to complex interventions frequently need not only to assess the efficacy of a given intervention but to identify which intervention - and which intervention components - might be most effective in particular situations. Here, intervention replication is rare, and commonly used synthesis methods are less useful when the focus of analysis is the identification of those components of an intervention that are critical to its success. Having identified initial theories of change in a previous analysis, we explore the potential of qualitative comparative analysis (QCA) to assist with complex syntheses through a worked example. Developed originally in the area of political science and historical sociology, a QCA aims to identify those configurations of participant, intervention and contextual characteristics that may be associated with a given outcome. Analysing studies in these terms facilitates the identification of necessary and sufficient conditions for the outcome to be obtained. Since QCA is predicated on the assumption that multiple pathways might lead to the same outcome and does not assume a linear additive model in terms of changes to a particular condition (that is, it can cope with ‘tipping points’ in complex interventions), it appears not to suffer from some of the limitations of the statistical methods often used in meta-analysis. The worked example shows how the QCA reveals that our initial theories of change were unable to distinguish between ‘effective’ and ‘highly effective’ interventions. Through the iterative QCA process, other intervention characteristics are identified that better explain the observed results. QCA is a promising alternative (or adjunct), particularly to the standard fall-back of a ‘narrative synthesis’ when a quantitative synthesis is impossible, and should be considered when reviews are broad and heterogeneity is significant. There are very few examples of its use with systematic review data at present, and further methodological work is needed to establish optimal conditions for its use and to document process, practice, and reporting standards.

/pdf/using-qualitative-comparative-analysis-qca-in-systematic-5gi5jt0a4h.pdf

Using qualitative comparative analysis (QCA) in systematic reviews of complex interventions: a worked example

Introduction The goal of this article is provide a first systematic review of the connection between public policy analysis and QCA techniques, with a core emphasis on the state-of-the-art in QCA empirical applications1. First, we present QCA both as an approach and as a set of techniques (crisp-set, multi-value and fuzzy-set QCA), stressing their specific characteristics. In a second section, we argue that, in several ways, there exists a preferential connection between QCA and public policy analysis: in terms of research design and also in terms of the actual goals and needs of policy-oriented research. Then, in the bulk of the article (sections 3 to 7), we provide an exhaustive survey of empirical applications published so far. To do so, we develop a typology of applications along two dimensions: the stages in the policy process (from agenda-setting and policy initiation to policy evaluation) and the level at which the 'cases' or units of analysis are empirically defined (from micro to macro). Finally, we wrap up this inventory by taking stock of what has been achieved so far. On that basis, we discuss some remaining limitations as well as some of the most promising avenues for further developments. Some precautionary notes must be made. To start with, this review is circumscribed to the field of public policy analysis, focusing on the action of public/state bodies with regards to concrete issues or societal demands - as indeed the domain of 'policy analysis' is much broader and could also encompass decision-making processes in private firms2 and other non-public players (e.g. Gill & Saunders 1992). Further, the purpose of this article is to focus on the concrete ways in which QCA has been used in the field. This requires that we provide some short indications on the research questions and research results for most of the applications, and therefore quite large sections of the article are rather descriptive by nature. Finally, this article does not aim at surveying the numerous technical issues and innovations in QCA (see rather Wagemann & Schneider 2010a, 2010b; Schneider & Wagemann forthcoming; Rihoux & Ragin 2009). Neither does it aim to provide 'quantitative' information on all the surveyed applications (e.g. number of cases, number of condition variables, ...) - this will be the purpose of a forthcoming article focusing on the broader population of QCA applications (Rihoux et.al. 2012 forthcoming). 1 QCA in a nutshell (3) 1.1 QCA as an approach QCA designates both an approach and an umbrella term for three specific techniques. The whole approach, as well as the first technique (csQCA - crisp-set QCA, first referred to as QCA) was launched by Charles Ragin's seminal volume (1987). QCA is first and foremost of comparative nature - more precisely: it was initially geared towards multiple case-studies, in a small- or intermediate-N research design. It thus strives to meet two apparently contradicting goals: gathering in-depth insight in the different cases and capture the complexity of the cases (gaining 'intimacy' with the cases), but also producing some level of generalization (Ragin 1987). The whole intention of Ragin (1987, 1997) was to develop an original "synthetic strategy" as a middle way between the case-oriented (or 'qualitative'), and the variable-oriented (or 'quantitative') approaches, which would "integrate the best features of the case-oriented approach with the best features of the variable-oriented approach" (Ragin 1987: 84). On the one hand, indeed, QCA embodies some key strengths of the case-oriented approach (Ragin 1987; Berg-Schlosser et.al. 2009). To start with, it is a holistic approach, in the sense that each individual case is considered as a complex whole which needs to be comprehended and which should not be forgotten in the course of the analysis. Thus, QCA is in essence a case-sensitive approach. Furthermore, QCA develops a conception of causality that leaves room for complexity. …

Qualitative Comparative Analysis (QCA) in Public Policy Analysis : An Extensive Review

In attempting to use a realistic evaluation approach to explore the role of Community Parents in early parenting programs in Toronto, a novel technique was developed to analyze the links between contexts (C), mechanisms (M) and outcomes (O) directly from experienced practitioner interviews. Rather than coding the interviews into themes in terms of context, intervention elements (mechanisms) and outcomes separately and which could be assembled into CMO configurations by the analyst, they were coded as linked dyads and triads directly from the practitioner narratives. Out of all of the linked codes entered, there were a maximum of three with the same combination, presenting challenges for typical qualitative data analysis. This article examines a novel technique that was developed in an attempt to expand this method beyond the circumstances described in the realistic evaluation literature to date. The bulk of the article focuses on the linked coding and analysis procedures, the challenges faced, and the ori...

http://journals.sagepub.com/doi/pdf/10.1177/1098214012440030

A New Realistic Evaluation Analysis Method Linked Coding of Context, Mechanism, and Outcome Relationships

Problem erkannt, aber nicht gebannt. Der Nutzen einer Verknüpfung von Konzept- und Umsetzungsevaluation am Beispiel der schweizerischen Strategie Migration und Gesundheit

Empfohlene Zitierung / Suggested Citation: Sager, Fritz ; Ledermann, Simone: Qualitative Comparative Analysis (QCA) und realistische Evaluation: Theoretische Parallelen und eine praktische Anwendung. In: Rehberg, Karl-Siegbert (Ed.) ; Deutsche Gesellschaft für Soziologie (DGS) (Ed.): Soziale Ungleichheit, kulturelle Unterschiede: Verhandlungen des 32. Kongresses der Deutschen Gesellschaft für Soziologie in München. Teilbd. 1 und 2. Frankfurt am Main : Campus Verl., 2006. ISBN 3-593-37887-6, 2048-2058.. https://nbn-resolving.org/urn:nbn:de:0168-ssoar-144025

Qualitative Comparative Analysis (QCA) und realistische Evaluation

Valorisierung von Politikberatung

Nutzung von Evaluationen in Regierung und Verwaltung

This article presents an innovative evaluation design which was used to evaluate the Swiss Environmental Impact Assessment. The design is new in that it amalgamates the realistic approach to evaluation with the method of Qualitative Comparative Analysis (QCA), the two of which are conspicuously similar. They share a complex view of causality, a generative perspective, a theory-driven approach to empirical observation and a limited claim to generalization. These conceptual parallels, as derived from the literature, are described in the first section, after a short introduction to realistic evaluation and the method of QCA. The following empirical section exemplifies their joint application and tackles the problems encountered. Based on this experience, the initial theoretical parallels are then reviewed. The article concludes that, under certain conditions, realistic evaluation and QCA provide a powerful tandem to produce empirically well-grounded context-sensitive evidence on policy instruments.

Realistic Evaluation and QCA: Conceptual Parallels and an Empirical Application

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