A SAS Macro for Generating Informative Cumulative/Point-wise Bar Charts
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1 Paper PO16 A SAS Macro for Generating Informative Cumulative/Point-wise Bar Charts Xuejing Mao, Eli Lilly and Company, Indianapolis, IN Mario Widel, Eli Lilly and Company, Indianapolis, IN ABSTRACT Bar charts are one of the most commonly used graphical tools for exploring categorical data. While the charts in different studies may differ in details, they are generated in essentially the same way. This paper describes a multi-purpose SAS macro that can generate customized bar charts automatically thereby eliminate unnecessary code writing. Specifically, this macro can generate cumulative or point-wise bar charts depending on the users requirements, automatically generate proper subtitles, footnotes, legends indicating significance across treatment groups at each time point, as well as the proper scale for the axes. Furthermore, if the statistical test indicates significant differences among more than two treatment groups, the macro will automatically generate another bar chart for the two groups with the lowest pairwise p-value. The macro is easy to use and rich in functionality. INTRODUCTION A picture is worth a thousand words. In statistical analysis, we use various graphs to explore the data or display complicated statistical results. Among the graphs, bar charts are one of the most commonly used. In different studies, the bar charts usually differ in kind and details. For example, sometimes we are interested in generating cumulative bar charts, but sometimes only point-wise bar charts make sense; we may want to add legends to the bar charts to indicate statistical significance across treatment groups at each time point; furthermore, if there is significant difference across all treatment groups, we may want to see a bar chart for the two groups with the lowest pair-wise p-value only. Despite all the technical differences, the bar charts are essentially made in the same way. Time and energy can be saved by using a general SAS macro to generate all bar charts. As a result, we developed a SAS Macro to generate customized bar charts depending on the users requirements. In this paper we illustrate how to use this macro by applying it on a simulated data set. First we ll describe the requirements on the format of the dataset, second we ll introduce the syntax of this macro, and at the end we ll show how to call this macro and present some sample output. SAMPLE DATE DESCRIPTION In order for the macro to work properly, the dataset should have the same format as shown in the following, trt patient event visit lastvisit
2 The dataset should contain variables TRT, PATIENT, EVENT, VISIT and LASTVISIT. The variables have the following meaning: TRT : a sequence of numbers starting at 1 indicating treatment group; PATIENT : Patient ID; EVENT : an event indicator, which is 1 for the patients who have event and 0 for patients who don t have event; VISIT : at which visit the event happened, it is a sequence of numbers starting at 1. For those patients who don t have event through the study, the value is missing. LASTVISIT : the last visit of the patient. In the dataset there should be one record per patient for all patients. In this sample dataset, we assume there are three treatment groups, namely trt1, trt2, and trt3; there are 500 patients in each treatment group and there are a total of 10 visits (visit 1 to visit 10). SAMPLE CALL OF SAS MACRO %BARCHART AND SAMPLE OUTPUTS Having prepared the data in the above way, we can call the macro %barchart to generate the desired bar charts. Macro %barchart has two parameters, namely DATAIN and CUorPW. The name of the dataset to be analyzed is assigned to parameter DATAIN. The parameter CUorPW takes two values, cu indicates that the customer wants a cumulative bar chart and pw indicates that the customer wants a point-wise bar chart. cu is the default value for parameter CUorPW. Suppose the sample dataset that we have is called event and we are interested in generating a cumulative bar chart. The macro call should be: %barchart(datain=event, CuorPW=cu) The output of the above macro call is as follows.
3 Because there are significant differences among these three treatment groups and Visit 7 has the smallest p-value (0.04) for three treatments statistical significant test, the Macro automatically generates the following point-wise bar chart for the two groups (treatment 2 and treatment 3) with the lowest pair-wise p-value (pvalue=0.06 for treatment1 vs. treatment2, p-value=0.08 for treatment2 vs. treatment3 and p-value= for treatment1 vs. treatment3) at visit 7.
4 If we are interested in generating a point-wise bar chart, the macro call is: %barchart(datain=event, CuorPW=pw) And the output of the above macro call is as follows. Because there are significant differences among these three treatment groups and Visit 7 has the smallest p-value (0.03) for three treatments test, the Macro automatically generates the following point-wise bar chart for the two groups (treatment 2 and treatment 3) with the lowest pair-wise p-value (p-value=0.06 for treatment1 vs. treatment2, p-value=0.05 for treatment2 vs. treatment3 and p-value=0.02 for treatment1 vs. treatment3) at visit 7.
5 DISCUSSION Normally, cumulative and point-wise bar charts are requested at the same time and there are many similarities in coding these two kinds of bar charts. With this macro, we can generate cumulative or pointwise bar chart. Redundant code will be avoided, time will be saved and we can response to our customers more quickly. Another advantage of this macro is that a point-wise bar chart for two groups with the lowest pair-wise p-value can be automatically generated. So the customer can get more information about the data. The disadvantage of the macro is that the current version can only generate bar charts to represent the count number of the event. If the variable in which the customers are interested in is continuous instead of discrete, this macro cannot be used. CONCLUSION In this paper, we present a SAS macro that can be used repeatedly to generate customized bar charts. With this macro, substantial gain in time and energy can be achieved by eliminating unnecessary code writing for generating bar charts, which in turn allows for faster response to our customers. The macro source code and code to simulate sample data will be available upon request. CONTACT INFORMATION Your comments and questions are valued and encouraged. Contact the author at: Xuejing (Susan) Mao Eli Lilly and Company, Lilly Corporate Center, Indianapolis, Indiana (317) maoxu@lilly.com Mario Widel Eli Lilly and Company, Lilly Corporate Center, Indianapolis, Indiana (317) mario_widel@lilly.com SAS and all other SAS Institute Inc. product or service names are registered trademarks or trademarks of SAS Institute Inc. in the USA and other countries. Indicates USA registration. Other brand and product names are trademarks of their respective companies.
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