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SigmaPlot Product Uses
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. Macro Concepts

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

1. Making the Graph Page the Currently Displayed Window

2. Using Statements from 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.

Scale Graph Macro [top]

B. Transforms

a. Rowwise Statistics Transform - This transform computes rowwise statistics. It complements the columnwise statistics available from the main menu. [top]

C. Graphs

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]

D. Analyses

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

iv. Transform [top]

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.

ii. Explicit Function Approximation

iii. Create These Functions

iv. Modify Equations in the SigmaPlot Fit Library [top]

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

j. Curve Fitting / Regression

k. Piecewise Nonlinear Regression - A four-segment piecewise linear equation is fit to rowwise replicate data.

l. ROC Curves Analysis

m. Standard Curves Analysis [top]

E. SigmaPlot & Excel

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]

F. SigmaPlot & MatLab

a. MATLAB® SigmaPlot® Functions [top]

G. Data Formats

a. Replicate Data Format

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]

 
 


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