| Macro Concepts | Transforms | Graphs | Analyses | Data Smoothing |
| Controlled Release Analysis | SigmaPlot & Excel | SigmaPlot & Matlab | Data Formats | Curve Fitting |
The following whitepapers highlight these application areas:
a. Creating a Macro
i. Recording a Macro – A tutorial showing how to record a macro that fits a decaying exponential curve to two data sets. The macro is then modified by 1) adding a for-loop, 2) adding a dialog to allow user control and 3) placing the macro name on the main menu.
ii. Creating a New Menu Item and Adding a Macro Name To It
iii. Run a Macro from the Toolbox Menu – Descriptions of the macros in the SigmaPlot Toolbox menu item.
iv. Adding a For-Loop to Your Macro
v. Adding a Dialog to a Macro – Describes how to create a dialog interface to a macro.
vi. Important Issues With Recorded Macros
b. Batch Processing using SigmaPlot Automation – Select a group of Excel files to process in a batch. This macro fits a user-selected SigmaPlot curve fit equation to the data, creates a graph and saves the results for all Excel files in a SigmaPlot notebook.
c. SigmaPlot Macro Sample Code – Useful macro sample code is provided for the user to copy. [top]
a. Rowwise Statistics Transform – This transform computes rowwise statistics. It complements the columnwise statistics available from the main menu. [top]
b. Transform Functions Root and Implicit – These two new functions have been added to solve equations. [top]
a. 2D Histogram – Histogram and cumulative histograms are created from a single column of data. Four graph types and other options are provided.
b. 3D Histogram – A three-dimensional bar-graph histogram is created from bivariate data.
c. Asymmetric Error Bars – This macro creates one of three types of graphs with asymmetric error bars from relative error bar data.
d. Preparing Your Graphs for Journal or Web Publication – A discussion of the graph file formats used and/or required for journal and web publication.
e. Quality Control Charts – Xbar and Range charts are created using the SigmaPlot Reference Line feature.
f. Ribbon Graph – This transform uses XZ profiles from XY Many Z data to generate the individual ribbons of a ribbon graph. This transform is located in your SigmaPlot Transforms folder.
g. Shade Between Two Curves – This macro creates a shade between two curves. It complements SigmaPlot’s built-in area plot feature that shades area under the curve to the X-axis. The macro assumes the data for both curves is strictly increasing in x.
h. Formatted SigmaPlot graphs for Submission to the FDA – The procedure is described for pasting SigmaPlot graphs into Microsoft Word that fit within specified margins and have a fixed font size. [top]
a. Analysis of Ligand Binding Data – Competition, saturation and dose-response studies may be analyzed with SigmaPlot Version 7.0 and this macro. Multiple replicate data sets are fit using an equation selected from a list of ten – and you may add your own. Graphical results, EC50 values and a statistical report are produced.
b. Analyzing Dissolution Test Data with SigmaPlot’s Excel Spreadsheet – An Excel worksheet analyzes up to 12 vessel by 6 sample time dissolution test data. Publication quality graphs of the results are simultaneously created. [top]
c. Shelf Life Time Analysis
i. Computing Shelf Life Time with SigmaPlot – An exact computation of shelf life time is computed and graph created. Four designs are available – lower specification only, upper specification only, lower and upper specification and degradant analysis.
ii. Validation of the Shelf Life Macro – Confirms accuracy of the Shelf Life Macro
iii. Simulation
d. Data Smoothing – Three real-world examples with increasing variability show the usefulness of SigmaPlot’s data smoothing algorithms to visualize the information in the data. [top]
e. Controlled Release Analysis
i. Fitting Controlled Release and Dissolution Data – Five controlled release models for analysis of drug dissolution data are implemented as a SigmaPlot fit library. One or all models may be easily fitted to your data.
f. Global Analysis of Concentration Response Curves – Global curve fitting without data concatenation is demonstrated.
g. Global Curve Fit of Enzyme Kinetics Data – A demonstration of simultaneous fitting of multiple functions to multiple data sets with shared parameters.
h. Global Curve Fitting for Ka and Kd from Sedimentation – A global analysis of ultracentrifuge radial macromolecule concentration gradients.
i. Global Curve Fitting – Dose Response Parallelism
k. Piecewise Nonlinear Regression – A four-segment piecewise linear equation is fit to rowwise replicate data.
l. Weight Functions in Nonlinear Regression
m. Parameter Confidence Intervals in Reports
a. Create a SigmaPlot Graph in Excel – An Excel macro that creates a SigmaPlot graph in Excel.
b. Using macros to place SigmaPlot charts in Microsoft – The macro statements required to insert a SigmaPlot graph into a PowerPoint slide are shown and explained. The similar procedure for placing a graph in Word is then shown. [top]
b. X,Y Many Z to X, Y, Z Format – This transform converts from one format to another. For example, the 3D smoothing algorithms requires data in XYZ format. [top]