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.

Most of the mixed methods functions can be found in the Mixed Methods menu tab. On the one hand, there are functions that link documents and document variables, for example, the topics from qualitative interviews with the variables of standardized interviews. With these functions, you can create so-called Joint Displays (Guetterman, Creswell, and Kuckartz, 2015), in which qualitative and quantitative data and/or results and conclusions are presented and analyzed together. On the other hand, MAXQDA offers functions that enable the transformation of code frequencies into document variables in order to subsequently use these for analysis, whether for the selection of qualitative data or for use in statistical procedures such as similarity analysis.

MAXQDA’s mixed-methods functions support all typical basic designs in mixed methods studies (Creswell and Plano Clark, 2018):

  • convergent Designs (qual. and quan. study parallel)
  • explanatory Designs (qual. study after quan.)
  • exploratory Designs (qual. study before quan.)

Further information about the mixed methods functions in MAXQDA and its methodology can be found here:

  • Kuckartz, U., & Rädiker, S. (2021). Using MAXQDA for mixed methods research. In R. B. Johnson & A. J. Onwuegbuzie (Hrsg.), The Routledge reviewer’s guide to mixed methods analysis (S. 305–318). Routledge. https://doi.org/10.4324/9780203729434-26
  • Rädiker, S. & Kuckartz, U. (2019). Analyse qualitativer Daten mit MAXQDA. Text, Audio, Video. Springer VS – speziell das Kapitel 13: https://doi.org/10.1007/978-3-658-22095-2_13
  • Guetterman, T. C., Creswell, J. W., & Kuckartz, U. (2015). Using joint displays and MAXQDA software to represent the results of mixed methods research. In M. T. McCrudden, G. J. Schraw, & C. W. Buckendahl (Hrsg.), Use of visual displays in research and testing: Coding, interpreting, and reporting data (S. 145–176). Information Age Publishing.
The “Mixed Methods” Tab

Overview of the Functions in the Mixed Methods Menu Tab

  • Activate Documents by Variables – Lets you activate documents to be included in further analysis such as Coding Query or Visual Tools 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 an interactive table, “codes x groups”, that allows you to compare coded segments for groups. These groups are formed by documents with selected variable values. 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.

Was this article helpful?