Phil Hearn: Blogger, Writer & Founder of MRDC Software Ltd.

How easy is it to convert a Quantum project to MRDCL?

Switching your main tabulation software platform from Quantum to MRDCL is not an easy decision, even when there may be 101 compelling reasons. There is likely to be a concern about moving projects, particularly large or complex ones. MRDCL might be more modern, more efficient and have all the power of Quantum (and more!), but this still leaves you with the problem of converting any existing Quantum projects to MRDCL. So, how does one mitigate these issues as far as possible? Fortunately, proven solutions are at hand.

Will MRDCL do everything Quantum does?

Often, this is the first question you want to ask. The answer here is YES. We do not have a single MRDCL customer who has converted from Quantum and has been unable to reproduce a Quantum table.

Why do we need to convert scripts?

The main reason for converting a Quantum script to MRDCL is because the script is used for a tracking study or is repeated, perhaps with a slightly modified questionnaire. To make matters worse, these projects are often the most complex, possibly with a history effectively documented in the Quantum code. Ideally, you will want this transition to be as smooth as possible and, more importantly, you will want consistent results produced in MRDCL.

The real problem with complex scripts

The biggest problem when converting a script from one language to another is working out what the more complex parts of the program scripts are doing. You are likely to find some script that you need to understand what it is doing or why it even exists. This is often exacerbated by the fact that the person left to convert the project may not be the original author.

A solution is at hand.

The first step is to export your Quantum project to SPSS. This will ensure that all the variables and data are available in a ‘clean’ state to bring into MRDCL. We previously offered a free SPSS utility that generated an MRDCL script for you from SPSS. However, in 2021, we introduced Intelligent Import to our MRDCL Central platform. Intelligent Import offers impressive features that make transfers fast and honed to improve productivity. Specifically:

  • Quick imports so your project is ready in seconds – ideal for simpler projects.
  • Controlled imports so that the variables generated can have rules applied (see more detail below)
  • Simple MRDCL code will produce easily understandable code, which may be helpful for less skilled staff or users new to MRDCL.
  • Advanced MRDCL code automatically generates shorthand MRDCL code, which will be easier to edit or change in future (recommended).

Let’s look at these features in more detail.

     1. Quick imports

Quick imports are ideal for simpler projects or when becoming familiar with MRDCL initially. With a single button press, MRDCL Central’s Intelligent Import tool will generate a working MRDCL script that will generate a table for every variable. If you want to add a banner to these tables, it is simple to specify a banner and apply it to all the tables. You can get from SPSS data to tables in Excel within one minute for most projects.


     2. Controlled imports

MRDCL’s Intelligent Import tool has two crucial tools that make project transfers from Quantum/SPSS to MRDCL more successful. Firstly, it deals with one of the fundamental flaws of storing projects in SPSS format. Whereas Quantum and MRDCL recognise multiple response variables, SPSS holds multiple response sets as a series of single response questions. In other words, SPSS will treat a list of fifteen brands a respondent may have bought as fifteen variables. Intelligent Import allows you to mark these variables so they are stored as one entity (variable), making analysis and data analysis much more straightforward. It’s a simple control to apply. Secondly, you can apply rules to groups of variables. For example, if variables q1_1 to q1_20 are twenty rating statements, there is a control you can apply so MRDCL knows that this is a bank of rating statements for a particular question.

Additionally, these easy-to-use controls are stored in a CSV file that you can edit the controls, if you wish, outside of MRDCL. It also means that if you make a mistake or forget to mark a control for one or more variables, you can rerun the Intelligent Import and produce a revised file in seconds.

     3. Simple/Advanced MRDCL code

By default, Intelligent Import produces simple MRDCL code with the script for each question generated in the order in which the variables are stored. However, there is an option to create advanced MRDCL code. Intelligent Import will automatically detect any repetitive blocks of script and generate shorthand MRDCL script as output. This will generally make the script easier to manage and edit in the future, although it may be more difficult for new users or juniors to understand. For example, it will mean that if you want to add a top two box to twenty rating statements, you will only need to make one change to the script rather than twenty repetitive changes. This makes it a valuable option to select in most cases.

What doesn’t work so well?

Two areas sometimes need further work even after using Intelligent Import’s helpful tools. Firstly, Quantum and SPSS do not per se make any filters applied to variables known. However, the data itself is filtered and ‘clean’. Let’s explain that more fully with an example. Let’s say Question 2 is filtered on respondents answering ‘Yes’ at Question 1. The respondent data will be ‘clean’, assuming it has been prepared correctly in Quantum. However, Quantum and SPSS do not pass on the information that Question 2 is only answered by respondents saying ‘Yes’ at Question 1. This means that if you tabulate Question 2 as it stands in MRDCL, the table would be based on all respondents and show the wrong percentages as typically required. There are two solutions – firstly, you can use an MRDCL format option (called ANR), which automatically filters tables on respondents answering a question, or alternatively, you can manually apply filters to tables, specifying that tables for Question 2 should only contain respondents saying ‘Yes’ at Question 1.

A second problem arises with complex tables, i.e. tables that are not basic crosstabs or summary tables. Quantum will not pass details of these tables on to MRDCL, which means that they may have to be reconstructed in MRDCL. This is usually the most onerous task for big or complex projects when converting from Quantum to MRDCL. However, MRDCL has some amazing tools to make this a lot simpler than it would be using Quantum, as you can make templates and shorthand script to generate most of these tables.

A third minor problem is that you may need to respecify any table controls, typically ones you want to apply to all tables. For example, the number of decimal places for percentages, which statistical options you want, etc.

Quantum to MRDCL using Triple-S


An alternative method is to use the Triple-S interchange format. There is a free utility provided by Cobalt Sky that allows you to convert Quantum scripts to Triple-S XML. MRDCL Central has an import tool from Triple-S, which has less flexibility than the SPSS project transfer tool but converts variables, texts and data into MRDCL script. This method generally works well for more straightforward projects and takes advantage of the fact that Triple-S ‘understands’ multiple response questions within its design.

What if I have data in Quantum binary format?


Although binary data is uncommon nowadays, if you have data in Quantum binary format, you can process it as it stands with MRDCL. You must rename the file with a .cbe file extension, which tells MRDCL that the data is in Quantum binary format. MRDCL can also process ASCII data, Excel data, CSV files or data from Access.

In summary

Converting projects from Quantum to MRDCL can be less time-consuming than it might first appear. Transferring variables, texts and data to MRDCL can be handled efficiently and quickly for most projects. Complex tables in Quantum will not be transferred to MRDCL as there is no bridge from Quantum to SPSS for tables. However, MRDCL has some excellent tools to minimise the time you spend. The important advantage of using the methods described in this article is that clean data can be carried over to MRDCL. Without this functionality, there is always the risk that figures will not precisely match the original figures in Quantum tables.

Help is always at hand.

As with many other advanced software products, there are other ‘tricks of the trade’, too detailed or specific to mention here, that can make project conversions easier than they might appear at first. Our support will be pleased to help with anything that seems onerous or time-consuming. Contact