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14.04.2016 admin
For a specific use case where you know the numbe of treatment groups, you can create a GTL program to display the data outside the plot area using data saved from the LIFETEST procedure as shown below. Now, we add two cells inside the LAYOUT LATTICE, each defined by a LAYOUT OVERLAY block. The upper cell has the graphical plots of the data, and the lower cell has the "At Risk" data shown as a table using the BLOCKPLOT statement. If you want the variable names rather than the numbers in the table you can change the code slightly, from class=stratumnum to class=stratum in the blockplot statement of the template.

After speaking with the the procedure writer, it was clear why the "at risk" table in the LIFETEST procedure template is not positioned outside.

I would like to print a header "At risk: " just above the at risk table, how can I do this ?

To add the header to the graph I showed, add an ENTRY statement with LOCATION=OUTSIDE in the lower LAYOUT OVERLAY. You cannot directly use my template, but you can use the ideas presented to update the template used by the LIFETEST procedure to modify the graph.

Important caveat: I am not an expert in proc LIFETEST, so the following is only a general guideline.

Example at somes terms if 12 have to be repeated 4 times I will only get the first 12 and the 3 others will be missing in the atrisk table. I guess the problem is inside the lower layout overlay but I did not find an issue to this matter.

Welcome to Graphically Speaking, a blog by Sanjay Matange focused on the usage of ODS Graphics for data visualization in SAS. The blog content appearing on this site does not necessarily represent the opinions of SAS.

The second step creates a macro variable whose value controls the size of the cells for plotting.

A few weeks back I posted an article on ways to create a WindRose Graph using SGPLOT procedure. A reader chimed in asking whether it was possible to create the graph shown on the right using a similar process. While I feel confident such data could be displayed in the manner shown on the right, it was not clear to me if this is indeed the best way. The "subgroup" values are harder to compare as it is not clear if they are represented by the radial value or the segment area. While the graph above is attractive, the information is may be easier to consume as a Likert graph shown on the right. Since both subgroup label and value are displayed in the segment, we have to compute the label, and its location to display the label using an overlaid TEXT plot. There was a recent comment on the original 'Unbox Your Box Plots', where a user wants to see the original data for the box, but only label the outliers.

As noted in the comment, labeling all the scatter markers and turning on the outlier display is not ideal. The process above is a bit tedious, so I figured I could use the power of SAS to create the graph I need as shown below. I created this graph by downloading the 2-year stock data for Face Book (FB) from the NASDAQ site.

I applaud the creativity of the user, who has clearly taken to heart the lesson that multiple plot statements can often be used creatively to build the graph you may want. While we have discussed AxisTables in earlier articles, it seems worthwhile to review the subject.

Note, since the CLASS option is used with the xAxisTable, the statistical values for the three levels of "Origin" are displayed stacked under each category on the x-axis. With SAS 9.40M3, the CLASSDISPLAY option was added to allow the display of the class values in the clustered arrangement as shown on the right. The benefit of this option is that multiple statistics can be displayed with such grouped plot statements. Finally, the user wanted to add vertical divider lines (column border) to separate the column of values.

Note, this visualization does not use a scatter plot, as was the case with the polar graph in the previous article. Note in the bar chart on the right, the bars are actually plotted using the High-Low plot, with Type=bar.

Using the equation shown above, we transform the (R, Theta) coordinates to the (x, y) coordinates. In the same data set, data is generated for the 16 radial grid lines, with values 0-315, the angle around the circle. In the previous article for Polar Graph, I had used GTL to display the circular grid lines using the EllipseParm statement. The directions are displayed using the N-S-E-W arrows, so understanding the information is easier. In the data step for the graph, x and y are computed from R and Theta using the following formula. A simpler method would be to just plot the Wind Speed and and Wind Direction on the Y and X axes of a rectangular XY plot as suggested at the start of the article.

Instead, we can also make the same graph using GTL, which does support the ELLIPSEPARM statement that can be used to draw the circular grids.

Note, I have used the option ASPECT=1.0 to ensure that the display area is circular regardless of the size or aspect of the graph itself.

While we have achieved one goal (inserting additional information into the graph), there are too many bars with small defect counts cluttering up the graph. In the code above, I have used the HBAR statement with the CATEGORYORDER=RESPDESC which creates this graph with the descending order of the bars. The full detailed data is provided to the procedure and the HBAR is computing the number of defects by product and arranging them by descending statistic (frequency). To create the graph shown on the right, I have to first compute the defect count for each product using PROC MEANS. One shortcoming for the graph above is that it does not scale well for moderately large data.

An alternate way which is relatively easy to build to view the same data is shown on the right. As you can see, this graph scales very well for all kinds of data, with small or large observation counts and for different number of categories on the x-axis.

Our focus here being on graphics, we were all extremely gratified by the presentations in the Data Presentation section. Amos Shu got us started with graphs for Adverse Event timeline graphs and panels in his paper Techniques of Preparing Datasets for Visualizing Clinical Adverse Events. Mayur Uttarwar and Murali Kanakenahalli proposed Developing Graphical Standards: A Collaborative, Cross-Functional Approach to ensure the correct list of Symbols and colors for the plots in the graph.

Stacey Philips presented a Swimmer Plot: Tell a Graphical Story of Your Time to Response Data Using PROC SGPLOT, displaying disease stages for each subject with additional information on the events. Kriss Harris presented Napoleon Plot for PharmaSUG and I Am Legend for PharmaSUG , presenting displays for assessing treatment safety, and ways to create just a legend, when the number of entries in the legend are too many to be included in one graph.

Jeffery Meyers presented Kaplan-Meier Survival Plotting Macro %NEWSURV which used the GTL layouts in creative ways to display loads of information in one plot or panel. Finally, I presented my paper from SGF 2014 -Up Your Game with Graph Template Language Layouts using GTL layouts to create complex custom graphs. This paper will get you started using the GTL layouts to go beyond the graphs you can create using the SGPLOT procedure. As usual, PharmaSUG lived up to its reputation of taking care of its attendees by providing fabulous food for breakfast, lunch and dinners. In addition to all the knowledge, I feel like I also gained 5 pounds. Thank you for listing me in this blog, and it was a lot of fun discussing graphs with you and the other presenters at the conference. In a previous article we discussed how to add axis aligned statistics table to a Lipid graph using GTL. Other graphs such as the Survival Plot also utilize the same technique to display the "at risk" statistics aligned by time or visits along the X axis.

Often, we also need to display columns of statistics aligned with the Y axis values as shown below. Step 1: The basic graph is created using a simple overlay of a band plot and a scatter plot as shown in the program and graph below. Yes, you can create a similar graph with GTL using the Layout Lattice with multiple columns. If you look through the articles in the blog, I am sure you will find many with statistics on the horizontal axis. I can't seem to find an example anywhere when the group option is used (such as this example). I wanted to customized the line color and pattern for grouped data and I tried to include some codes to define my style (see below), not sure what I was missing but I can't make that happen. These are used because I made this into a macro that will download the data, process it, and create multiple graphs given the stock name and symbol. The syntax from proc gplot doesn't apply to KM plots and I can't edit the axes text or positioning in the graph editor. How do i plot a mean curve of body weight over time if i want one yaxis to be in kg and the otherwww yaxis to be in pound ?

Since you've already provided this horizontal example, what about a vertical example with the summary stats below the graph along the horizontal (time) axis?

After speaking with the the procedure writer, it was clear why the "at risk" table in the LIFETEST procedure template is not positioned outside.

I would like to print a header "At risk: " just above the at risk table, how can I do this ?

To add the header to the graph I showed, add an ENTRY statement with LOCATION=OUTSIDE in the lower LAYOUT OVERLAY. You cannot directly use my template, but you can use the ideas presented to update the template used by the LIFETEST procedure to modify the graph.

Important caveat: I am not an expert in proc LIFETEST, so the following is only a general guideline.

Example at somes terms if 12 have to be repeated 4 times I will only get the first 12 and the 3 others will be missing in the atrisk table. I guess the problem is inside the lower layout overlay but I did not find an issue to this matter.

Welcome to Graphically Speaking, a blog by Sanjay Matange focused on the usage of ODS Graphics for data visualization in SAS. The blog content appearing on this site does not necessarily represent the opinions of SAS.

The second step creates a macro variable whose value controls the size of the cells for plotting.

A few weeks back I posted an article on ways to create a WindRose Graph using SGPLOT procedure. A reader chimed in asking whether it was possible to create the graph shown on the right using a similar process. While I feel confident such data could be displayed in the manner shown on the right, it was not clear to me if this is indeed the best way. The "subgroup" values are harder to compare as it is not clear if they are represented by the radial value or the segment area. While the graph above is attractive, the information is may be easier to consume as a Likert graph shown on the right. Since both subgroup label and value are displayed in the segment, we have to compute the label, and its location to display the label using an overlaid TEXT plot. There was a recent comment on the original 'Unbox Your Box Plots', where a user wants to see the original data for the box, but only label the outliers.

As noted in the comment, labeling all the scatter markers and turning on the outlier display is not ideal. The process above is a bit tedious, so I figured I could use the power of SAS to create the graph I need as shown below. I created this graph by downloading the 2-year stock data for Face Book (FB) from the NASDAQ site.

I applaud the creativity of the user, who has clearly taken to heart the lesson that multiple plot statements can often be used creatively to build the graph you may want. While we have discussed AxisTables in earlier articles, it seems worthwhile to review the subject.

Note, since the CLASS option is used with the xAxisTable, the statistical values for the three levels of "Origin" are displayed stacked under each category on the x-axis. With SAS 9.40M3, the CLASSDISPLAY option was added to allow the display of the class values in the clustered arrangement as shown on the right. The benefit of this option is that multiple statistics can be displayed with such grouped plot statements. Finally, the user wanted to add vertical divider lines (column border) to separate the column of values.

Note, this visualization does not use a scatter plot, as was the case with the polar graph in the previous article. Note in the bar chart on the right, the bars are actually plotted using the High-Low plot, with Type=bar.

Using the equation shown above, we transform the (R, Theta) coordinates to the (x, y) coordinates. In the same data set, data is generated for the 16 radial grid lines, with values 0-315, the angle around the circle. In the previous article for Polar Graph, I had used GTL to display the circular grid lines using the EllipseParm statement. The directions are displayed using the N-S-E-W arrows, so understanding the information is easier. In the data step for the graph, x and y are computed from R and Theta using the following formula. A simpler method would be to just plot the Wind Speed and and Wind Direction on the Y and X axes of a rectangular XY plot as suggested at the start of the article.

Instead, we can also make the same graph using GTL, which does support the ELLIPSEPARM statement that can be used to draw the circular grids.

Note, I have used the option ASPECT=1.0 to ensure that the display area is circular regardless of the size or aspect of the graph itself.

While we have achieved one goal (inserting additional information into the graph), there are too many bars with small defect counts cluttering up the graph. In the code above, I have used the HBAR statement with the CATEGORYORDER=RESPDESC which creates this graph with the descending order of the bars. The full detailed data is provided to the procedure and the HBAR is computing the number of defects by product and arranging them by descending statistic (frequency). To create the graph shown on the right, I have to first compute the defect count for each product using PROC MEANS. One shortcoming for the graph above is that it does not scale well for moderately large data.

An alternate way which is relatively easy to build to view the same data is shown on the right. As you can see, this graph scales very well for all kinds of data, with small or large observation counts and for different number of categories on the x-axis.

Our focus here being on graphics, we were all extremely gratified by the presentations in the Data Presentation section. Amos Shu got us started with graphs for Adverse Event timeline graphs and panels in his paper Techniques of Preparing Datasets for Visualizing Clinical Adverse Events. Mayur Uttarwar and Murali Kanakenahalli proposed Developing Graphical Standards: A Collaborative, Cross-Functional Approach to ensure the correct list of Symbols and colors for the plots in the graph.

Stacey Philips presented a Swimmer Plot: Tell a Graphical Story of Your Time to Response Data Using PROC SGPLOT, displaying disease stages for each subject with additional information on the events. Kriss Harris presented Napoleon Plot for PharmaSUG and I Am Legend for PharmaSUG , presenting displays for assessing treatment safety, and ways to create just a legend, when the number of entries in the legend are too many to be included in one graph.

Jeffery Meyers presented Kaplan-Meier Survival Plotting Macro %NEWSURV which used the GTL layouts in creative ways to display loads of information in one plot or panel. Finally, I presented my paper from SGF 2014 -Up Your Game with Graph Template Language Layouts using GTL layouts to create complex custom graphs. This paper will get you started using the GTL layouts to go beyond the graphs you can create using the SGPLOT procedure. As usual, PharmaSUG lived up to its reputation of taking care of its attendees by providing fabulous food for breakfast, lunch and dinners. In addition to all the knowledge, I feel like I also gained 5 pounds. Thank you for listing me in this blog, and it was a lot of fun discussing graphs with you and the other presenters at the conference. In a previous article we discussed how to add axis aligned statistics table to a Lipid graph using GTL. Other graphs such as the Survival Plot also utilize the same technique to display the "at risk" statistics aligned by time or visits along the X axis.

Often, we also need to display columns of statistics aligned with the Y axis values as shown below. Step 1: The basic graph is created using a simple overlay of a band plot and a scatter plot as shown in the program and graph below. Yes, you can create a similar graph with GTL using the Layout Lattice with multiple columns. If you look through the articles in the blog, I am sure you will find many with statistics on the horizontal axis. I can't seem to find an example anywhere when the group option is used (such as this example). I wanted to customized the line color and pattern for grouped data and I tried to include some codes to define my style (see below), not sure what I was missing but I can't make that happen. These are used because I made this into a macro that will download the data, process it, and create multiple graphs given the stock name and symbol. The syntax from proc gplot doesn't apply to KM plots and I can't edit the axes text or positioning in the graph editor. How do i plot a mean curve of body weight over time if i want one yaxis to be in kg and the otherwww yaxis to be in pound ?

Since you've already provided this horizontal example, what about a vertical example with the summary stats below the graph along the horizontal (time) axis?

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