General Information about Mixed Methods in MAXQDA

MAXQDA is one of the pioneers in the field of method integration. Functions for combining qualitative and quantitative data are already found in the very first versions of the program in the late 1980s and early 1990s. With the option to manage a data set of standardized, quantitative data parallel to the texts, the foundation was laid. Since version 10 there is a further tool in the form of code variables, which allows the definition of variables below the case level of a document and since version 12.2 there is a fully integrated statistics package “Stats” for carrying out descriptive and inferential statistical calculations, the results of which can be used directly for the integrative analysis of qualitative data.

In the Mixed Methods Tab, functions are available which either link documents and variables, e.g. the topics from qualitative interview material with the variables from standardized interviews, or which carry out quantitative evaluations based on the coding carried out. The first are so-called joint displays in which both qualitative and quantitative data, results or conclusions are presented together. Guetterman, Creswell and Kuckartz (2015) present various mixed method designs and suitable joint displays in an overview article. MAXQDA offers several joint displays suitable for common mixed method designs. These designs include in particular

  • Convergent Designs (qual. and quan. study parallel)
  • Explanatory Designs (qual. study after quan.)
  • Exploratory Designs (qual. study before quan.)

The “Mixed Methods” Tab

Overview of Mixed Methods Functions

  • Activate Documents by Variables – lets you activate documents to be included in the Coding Query based on document variable values. You could, for example, use this function to identify what men between the ages of 40 and 50 said about migration issues.>
  • Interactive Quote Matrix – creates a Word file showing what different groups said about a theme based on certain variable values that you specify. Each group’s coded segments for the specified codes are in a different column. You could, for example, choose to see how those with various levels of education differ on their approach to combating homelessness.
  • Crosstab – works parallel to the Code Matrix Browser, except that this function doesn’t work on the document level. Instead, you can create groups based on your variable values and compare how often each of these groups talks about each theme. You could, for example, compare how often men talk about relationships in your life satisfaction interviews in comparison to women.
  • Quantitizing – This is the transformation of qualitative coding information into quantitative variables. Quantitizing allows you to store the code frequencies as document variables, such that for each document you have information about how often a code appears in that document. This information can then be analyzed statistically or used for the selection of cases.
  • Typology Table – shows an overview of variable values for qualitative typologies that you have created (e.g. for people with various views on combating their own homelessness). You could see, for example, what the mean age, gender breakdown, and average time already homeless is for the “apathetic pessimists” in comparison to the “proactive optimists.”
  • Similarity Analysis for Documents – selected documents are analyzed on the basis of existing coded segments and document variables for their similarity, and the results are presented in a similarity or distance matrix.
  • Side-by-side Display of Results – This joint display compares the results of a qualitative study with those of a quantitative study.
  • QUAL Themes by QUAN Groups – This joint display is used to compile coded segments or summaries in a table for groups formed on the basis of variable values.
  • Statistics by QUAL Groups – The result of this function corresponds to the typology table and divides documents into groups according to codes assigned to them. This joint display allows you to compare average values, standard deviations and absolute and relative frequencies of selected variables for these groups.

In the “Code System” window there are functions available, that allow you to use the code frequencies for each document as document variables:

  • Transform code into document variable or categorical document variable – Codes can be added as document variables that specify how often the code occurs in the document (“Quantitizing” as described above) or which subcode occurs most frequently in a document. The latter is particularly useful for evaluative qualitative content analyses.