Three potential CAQDAS functions might be particularly useful for the integration of quantitative methods into qualitative research:

1. Word counts, in particularly when combined with lemmatizations (word stemming), might reveal useful hints for potential keyword codes.
2. Crosstabulations and word maps might identify themes in the data.
3. Most importantly, the export of data, such as code frequencies across documents, enables statistical analyses withe the appropriate external software.

In contrast, the possibility to directly perform more complex quantitative content analyses within CAQDAS, while convenient, can take a backseat, if the latter data exchange facilities are offered. At any rate, currently only QDA Miner, which is integrated in the Simstat Suite for statistical analyses offers such functionality. As displayed in below table, which summarizes the statistical facilities offered by the different CAQDAS, all of the programs offer unproblematic transfer of their data to statistical packages and spreadsheets, once the data have been generated. The major differences therefore lie in the ease of data generation.

Most programs (with the exception of NVivo and Qualrus) allow for the display of simple word frequencies. ATLAS.ti and MAXqda with its plug-in MAXdictio allow moreover for the usage of manually defined stop word lists, an essential tool for all quantitative analyses. QDA Miner goes even a step further, as it contains inbuilt and links to dictionaries.

QDA Miner is also the most sophisticated program, when it comes to the analyses of co-occurrences of codes and/or strings, as it not only allows for the visualization of co-occurrence matrixes, but also for a number of clustering methodologies. All newer CAQDAS allow for some visualization of co-hierarchy matrices; NVivo, for instance, colors co-occurrences darker, the more frequent they are.

Finally, a major consideration in the use of CAQDAS for mixed methods is their speed, which will be discussed in the next section.

1. ATLAS.ti's Word Cruncher took more than three hours to perform its task onto approximately 2,000 documents with maximum 10KByte size.
2. Comma or tab delimited files are plain text files, which can be read by virtually all statistical and office applications.