Text variables, categorizing

Clinical trial data come to the statistical programmer in two basic forms numeric variables and character string (text) variables. With this in mind, there are two considerations for all numeric and text variables. All data should be cleaned if they are needed for analyses, and any data entered asfree-text variables should be coded or categorized if they are needed for analyses. 

Clinical trial data come in two basic forms numeric variables and text variables. Numeric variables are easy for the statistical programmer to handle. Numbers can be analyzed with SAS in a continuous or categorical fashion without much effort. If a numeric variable needs categorization, it is easy enough to categorize the data within SAS. For example, if you had to classify patient age, a simple DATA step such as the following might serve well. 

The problem for the statistical programmer in categorizing data comes from text variables, or more specifically, free-text variables. A free-text variable is one that may contain any characters and is typically limited only in length. As an example, let s say you need to summarize the adverse events for a set of patients in a trial. The following SAS code shows the data and a quick summarization of the adverse events. 

In summary, for data to be useful in clinical trial analyses they need to be quantifiable. The data must be either a continuous measure or a categorical value. Free text poses a problem for analysis, and if it is a valuable variable for the statistical analyses it really must be coded. Finally, hardcoding should be used only when absolutely necessary, because it is inherently problematic. Organizations that do allow hardcoding should document in their standard operating procedures (SOPs) that it is an approved business practice and how it is to be used. 

In statistics, the two-way analysis of variance (ANOVA) test examines the influence of different categorical independent variables on one dependent variable. The two-way ANOVA can determine the main effect of contributions of each independent variable and also identify if there is a significant interaction effect between the independent variables. The preliminary text study examines if the consistency of the answers is influenced by team and/or by case, and if the ethical theory chosen to analyze an ethical dilemma is influenced by team or by case. The influence of gender, year of study (senior, junior, etc.), country of birth, and value profile of the team members were not examined due to a small sample size. 

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