Benchmark Dose Software (BMDS)
III. Benchmark Dose Software (BMDS)
Navigation
- User-friendly interface for 25 models (including alternative dichotomous models)
- Output tailored to EPA draft BMD guidelines
- Model Description and list of chosen options
- Goodness-of-fit information
- BMD & BMDL
- Graphs and Summary Reports
- Toolbar & File Menu
- Edit Menu
- View Menu
- Tools
- Session Grid
- Windows
- Help Menu
New Session
Create a new session
Open Session
Load an existing session
Save Session
Save the current session
Save Session As...
Save a new version of the current session
New Dataset
Create a new dataset
Open Dataset
Load a dataset
Print
Print the current session
Exit
Exit the application
The View Output icon is found in the tool bar. The View Output option can also be found under the Tools menu.
View Output File
Load a text output file (*.out)
Cut (Ctrl+X)
Selected data is cut to clipboard
Copy (Ctrl+C)
Selected data is copied to clipboard
Paste(Ctrl+V)
Clipboard data is pasted at cursor
Delete (Del)
Selected data is deleted
Select All (Ctrl+A)
All data is deleted
Data can also be cut, copied and pasted from Excel and Lotus.
These options customize the appearance of the BMDS interface.
Tool Bar
Toggling the tool bar option determines if the tool bar icons below the main menu are displayed or hidden.
Status Bar
Toggling the status bar option determines if the status bar at the bottom of the screen is displayed or hidden.
View Plot...
Displays a designated plot file (*.plt)
View Output File
Displays an designated output file (*.out)
R Interface
Used for working with ToxicoDiffusion models
Options...
Reveals option tabs for application configuration.
The following options are available:
Report
Summary Report
A checkmark to the right of this option indicates a summary report and summary plots will be displayed after a session "run." If left unchecked, the summary report is not generated and plots displayed in separate windows.
Group By
This option determines how session "run" results (summary reports and summary plots) are grouped together. Results can be grouped by end points or the data filename.
Data Grid
Default Number of Rows
Determines how many preferred rows appear when creating a new dataset.
Default Number of Columns
Determines how many preferred columns appear when creating a new dataset.
Work Directory
Option under this tab are currently not implemented.
This menu is avaialbe when a session window is open.
Insert Row
Inserts a new row above the currently selected row in the session grid. The currently selected row is indicated by the black arrow to the left of the row number.
Drop down list
Allows a predefined number of rows to be added to the session grid or all the models of a chosen group to be added.
Add Row(s)
Used in conjuction with the drop down list described above. No action is taken until user selects from the list and clicks Add Row(s).
Delete Row
Deletes the currently selected row in the session grid.
Tile Horizontal
Tiles windows horizontally.
Tile Vertical
Tiles windows vertically.
Cascade
Displays windows in a cascade arrangement.
Close all
Closes all windows inside the BDMS program.
Window List
A list of currently open windows is displayed. Clicking on a particular window name will bring the selected window to the top. The current top window will have a checkmark to the left of its name.
BMDS 2.0 Help
Displays the contents of the Help documentation in a new window.
Dichotomous Alternative Models Help
Information on the Alternative models is displayed in a new window.
Submit Problem Report
Opens an internet browser to the BMDS Issue Reporting ticket system. This feature allows software issues to submitted and their status tracked online.
About...
Window describing the BMDS Sponsors and Credits, BMDS program version, and a disclaimer.
- Editing Data
- Transforming a Data Column
- Saving Data
- Load/Importing Data
- Exporting Data
Data can also be exported to a file in the text, comma, and space delimited formats using the Export Data To option in the dataset File menu.
A Blank spreadsheet displays when "New Dataset " option is selected. Data can be pasted into the spreadsheet from Excel and Lotus programs.
To change a column header right-click on the column header with the mouse button and select Rename Column.
Cutting and Pasting
Use cut (Ctrl+X), copy (Ctrl+C), paste (Ctrl+V) and Undo (Ctrl+Z) in
normal manner.
Deleting Columns and Rows
Highlight entire column or row and hit Delete key. Alternatively use the Data Grid menu in the dataset window to select Delete Column or Delete Row.
Adding Columns and Rows
Use the Data Grid menu in the dataset window to select options to Insert Row or Insert Column before the currently active row or column. Multiple columns and rows can be added to the end of spreadsheet by using the Add Row or Add Column options.
Sorting
Data sets can be sorted by data in any column by clicking in the column headers.
To transform a data column right-click the right mouse button on an empty column header where you want the new (transformed) data to appear and choose Transform Column.
Choose the type of transformation to be performed, select the column(s) to be acted upon and enter an X factor (if appropriate).
New data sets are assigned default name of "Unsaved.dax." The Save Dataset menu option must be used to assign a meaningful file name and save the data.
Save Dataset saves file to name/location.
Save Dataset As causes BMDS to prompt for filename and location. New file is saved as a BMDS dataset with .dax extension.
Selecting Import Data From in the dataset window File menu opens a submenu with a selection of file types from which data can be imported.
| TYPE | EXTENSION |
|---|---|
| BMDS 1.xx Dataset (delimited with blank) | *.SET |
| MS Excel Version 2003 | *.XLS |
| Text File Delimited with Space | *.TXT |
| Text File Delimited with Commas | *.CSV |
| Text File Delimited with Tab | *.TXT |
In BMDS there are two ways to run models. The first method is to run a single model on a particular dataset through the dataset window. This procedure is described in the section below. The second method is to run models through the session window which is described in section F. Running Sessions.
- Selecting a Model
- Defining Variables
- Viewing Graphic Output
- Viewing Text Output
Model Type
Select from four model types, Continuous, Dichotomous, Dichotomous Alternative and Nested Dichotomous .
Model Name
Select from list of models available for the model type.
Proceed
This button opens an option screen allowing the user to set various parameters before the model is run. The option screen appears below in section 2.
Required variables depend upon the model type selected.
Dichotomous
Dose, Subjects in Group , and Incidence or % Positive.Continuous
Dose, Subjects in Group, Mean & Standard Deviation; or Dose and Response for individual data.Nested Models
Dose, Litter Specific Covariate, Incidence and Litter Size.
Dose
Variable representing the amount of a substance an experimental subject consumes (e.g., oral drinking water or food studies), is injected with (e.g., gavage or intravenous injection studies) or is exposed to (e.g., inhalation studies). For inhalation studies, this column would represent the concentration of the substance in the air being inhaled. Alternatively dose could be an internal metric of exposure (e.g., blood levels of the parent compound or metabolite) measured or predicted by a PBPK model. Most of the time Dose will be an independent variable under the control of the experimenter. However, for epidemiological studies Dose, as well as confounding factors such as age, smoking habits and duration of exposure, are not under the control of the experimenter and may be different for each individual responder. While BMDS allows for the entry and analysis of individual Dose information, provisions for factoring the impact of confounders have not as yet been incorporated.
#Subjects in Dose group (continuous and dichotomous data)
Independent variable representing the total number of subjects within a dose group for which a continuous Individual Response is measured or dichotomous Positive Responses are identified.
Incidence (dichotomous and nested data)
Dependent variable used for Dichotomous and Nested Models to represent the number of subjects within a Dose group responding in a positive, generally considered adverse, manner.
% Positive (dichotomous data)
Dependent variable used for Dichotomous Models to represent the percent of the total number of subjects within a Dose group that responded positively. The data for this column must be entered as a percent (not a fraction).
Mean (continuous data)
Dependent variable used for Continuous Models to represent the average response within a group (sum of all responses in group divided by Subjects/Group).
Standard Deviation (continuous data)
The positive square root of the variance for a Dose group, which is the sum of the squared deviations of the individual responses from the mean, divided by # Subjects in Dose Group-1.
Individual Response (continuous data)
This dependent variable refers to the individual continuous data responses by subject. If this variable is used, the Subjects/Group, Mean and Standard Deviation continuous data variables are not used and are grayed out.
Litter Size (nested data)
Number of subjects per litter for which the end-point is measured.
Litter Specific Covariate (nested data)
This is a covariate such as body weight of dams, number of implants or litter size that is felt to best explain response variability between litters. It is used in the nested models to try to account for that variability.
Since only one model at a time can be run through the dataset screen, the output is a single plot with associated text output. In section F. Running Sessions, multiple models are run simultaneously and output is displayed in a grouped format. In addition to the grouped format display, a single model plot and its associated text output can be selected and viewed as shown below in a session as well. See section F. Running Sessions for further explanation.
The BMD and BMDL are the green vertical lines associated with a benchmark response (BMR), the horizontal green line.
The BMD curve is red and BMDL "curve" is blue.
Data Points and dose group confidence intervals are green.
Displays can be modified using Wgnuplot edit features another application capable of vector graphic editing (e.g., PowerPoint).
Individual graphs my be copied to the clipboard and inserted into other documents such as MS Word. Use right-click on the mouse over a plot and select Copy to Clipboard.
The plot and text output may be viewed separately after the model has been run by using the Tools main menu and select View Plot... or View Output File...
".out" files provide goodness-of-fit criteria to aid in determining the appropriateness of the subject model to BMD.
Parameters are estimated using Maximum Likelihood procedures through an iterative routine. There is no guarantee that the model parameters will achieve true maximization. The output pages should assist the user in determining whether or not it was achieved.
Output Format
There are some differences depending on model type. BMDS Help Manual describes output formats for
Dichotomous, Continuous, Nested, and Dichotomous Alternative models.
When results differ for two runs from the same dataset and model, users can compare output pages to determine if the model settings or the model versions were different.
This section assumes that you have a basic working knowledge of the capabilities of dichotomous, nested and continuous models. You are encouraged to read the sections in the BMDS user manual that describe these types of models before proceeding.
- Dichotomous Model Options
Dose Groups
This is a read-only field indicating the number of Dose groups recorded from the data set file for input into the model.Risk Type
Choices are "Extra" (Default) or "Added." Added risk is the additional proportion of total animals that respond in the presence of the dose, or the predicted probability of response at dose d, P(d), minus the predicted probability of response in the absence of exposure, P(0). Extra risk is the additional risk divided by the predicted proportion of animals that will not respond in the absence of exposure, 1 - P(0). Thus, extra and additional risk are equal when background rate is zero.BMR
The benchmark response (BMR) is entered here (in regular or scientific notation format), and represents the user designated fractional increase in added or extra risk (Default = 0.1) that will be used to derive the benchmark dose (BMD) and the benchmark dose’s lower bound confidence limit (BMDL). Note that the response associated with the BMR that is displayed in the model output will only be the same as the BMR when P(0) = 0. This is because to obtain the actual response value one must solve for P(d) in the equation for added or extra risk discussed above.Restrict Slope >= 1
(Log-Logistic and Log-Probit only): If the slope is allowed to be less than 1, the slope of the dose-response curve is infinite at zero dose.Restrict Power >= 1
Gamma , Weibull , Log-Logistic and Log-Probit models only. Selecting this feature (Default) restricts the power parameter (α) to a value of 1 or greater. If α < 1, then the slope of the dose-response curve becomes infinite at the control dose. This is biologically unrealistic, and can lead to numerical problems when computing confidence limits, so several authors have recommended restricting α >= 1. As in the Crump Weibull model (Threshw, 1990) the number of degrees of freedom assumed by the model are not reduced, even though the power parameter is only partially restricted (the power parameter is actually estimated when it converges above a value of 1).Degree Poly
Multistage model only This is the degree of the polynomial model that will be used, or the number of times dose is factored into the model equation (maximum = 23). A value must be entered here before the model will run. Polynomial degree should not exceed the number of dose groups unless the beta coefficients of the model are restricted (beta coefficients are always restricted in the cancer model).Restrict betas >= 0
Multistage model only. Selecting this feature (Default) restricts all of the beta (β) parameter coefficients in the multistage model to a value of 0 or greater. As with the power parameter, assumed degrees of freedom are not reduced, even though this results in only a partial restriction on the parameters being estimated. - Dichotomous Model Text Output
- Nested Model Options
Restriction
Power parameter P (Rho) can be restricted to be > 1 (Default)Risk Type
Choices are "Extra" or "Added." Additional risk is the additional proportion of total animals that respond in the presence of the dose, or the probability of response at dose d, P(d), minus the probability of response in the absence of exposure, P(0). Extra risk is the additional risk divided by the proportion of animals that will not respond in the absence of exposure, 1 - P(0). Thus, extra and additional risk are equal when background rate is zero.Fixed Litter Size
Choices are "Control Group Mean" (Default) or "Overall Mean." Nested Model Descriptions for an explanation as to why this option is necessary, and which choice would be preferred for your given data set. Basically, If the Litter Specific Covariate is not affected by dose, the Overall Mean should be used. If the Litter Specific Covariate is affected by dose, consider using the Control Group Mean.Litter Specific Covariate
Provides user with the option to allow the models to attempt to account for a litter specific covariate or not. If "Use Litter Specific Covariate" is selected (Default), all of the Theta values are estimated (set to -9999 in the model input file). If "Don't Use Litter Specific Covariate" is chosen, all of the Theta values are set to zero.Intralitter Correlations
Provides user with the option to allow the models to attempt to estimate intralitter correlations or assume they are zero. If "Estimate Intralitter Correlations" is selected (Default), all of the Phi values are estimated (set to -9999 in the model input file). If "Assume Intralitter Correlations Zero" is chosen, all of the Phi values are set to zero.BMR
The benchmark response (BMR) is entered here (in regular or scientific notation format), and represents the user designated fractional increase in added or extra risk (Default = 0.1) that will be used to derive the benchmark dose (BMD) and the benchmark dose’s lower bound confidence limit (BMDL). Note that the response associated with the BMR that is displayed in the model output will only be the same as the BMR when P(0) = 0. This is because to obtain the actual response value one must solve for P(d) in the equation for added or extra risk discussed above. - Nested Model Text Output
- Continuous Model Options
- Continuous Model Text Output
- Test 1 (A2 vs. R): Assumes that response & variances don't differ among dose levels. If this test accepts, there may not be a dose-response.
- Test 2 (A1 vs. A2): Assumes that variances are homogeneous. If this test accepts, the simpler constant variance model may be appropriate.
- Test 3/4 (Fitted vs. A3; Test 4 in Non-constant variance model): Assumes that the model for the mean fits the data. If this test accepts, the user has support for the choice of model.
- Test 3 (A3 vs. A2; Non-constant variance model): Assumes that variances are adequately modeled. If this test accepts, it may be appropriate to conclude that the variances have been modeled appropriately.
Generally includes model version number, date and time of run, input data set used, form of the response function, model option choices, and result summaries (e.g., goodness-of-fit data). Allows for accurate reproduction of model runs at a later date (e.g, to check new models or to verify the work of other individuals).
Default Initial Parameters
Parameter starting points for the iterative maximization routine used by BMDS.
Parameter Estimates
Final parameter estimates and standard errors determined by the model.
Asymptotic Correlation Matrix of Parameter Estimates
Matrix of correlation estimates between each of the parameters.
Analysis of Deviance Table
Provides maximum likelihood (MLE) values for "full," "fitted" and "reduced" models. The Full model is a one that perfectly fits all positive response proportions at dose levels specified. The Fitted model is the selected model, using the estimated parameter values. The Reduced model assumes the effect is the same at all dose levels. Deviance, degrees of freedom, and P-values are also reported for each model.
AIC Value
Akaike Information Criterion; can be used to compare models. Equal to -2x(log-likelihood - degrees of freedom or number of parameters estimated).
Goodness of Fit
Lists data and Chi-Square Goodness of Fit results.
Chi-Squared Residuals
Numerical differences between observed and estimated effects used to evaluate fit at low doses.
Benchmark Dose Computation
BMD and BMDL values
Text Output for the BMDS Nested Models is similar to the output for the BMDS dichotomous models with one notable exception. The BMDS nested model output file contains two Goodness of Fit tables, one for litter data and one for grouped data.
Goodness of Fit Information - Litter and Grouped Data Tables. Both of these tables provide a listing of the data, expected and observed responses and Chi-Square residuals (observed - expected). The "Litter Data" table contains this information for each litter. To obtain the "Group Data" table, the Litter Data were sorted on Dose (first), and by Litter Specific Covariate within Dose. Within dose, litters adjacent to each other with respect to Litter Specific Covariate were grouped together until the expected number of affected pups was at least one. This grouping was done prior to the estimation of an overall Chi-Square and p-value to improve the validity of the Chi-Square approximation for the goodness of fit statistic.
Restrictions - Linear, Polynomial and Hybrid models
Restriction on Beta coefficients can be "None" (Default), "Non-negative" or "Non-positive". Power model, - power parameter (Rho) can be restricted to be >= 1. Hill model, - n parameter can be restricted to be > 1.
Adverse Direction
Automatic (Default) = BMDS chooses. "Up" or "Down" = choices for direction of increased adversity
along response curve. The choice determines how the BMD will be derived; it does not impact curve fitting.
| Rel. Dev. | BMR = P0 " (BMRF*P0) (Default) |
| Abs. Dev. | BMR = P0 " BMRF |
| Std. Dev. | BMR = P0 " (BMRF*STD) |
| Point | BMR = BMRF |
| Extra (Hill only) | for "up," BMR = P0 + (BMRF*(Pmax - P0) for "down,"BMR = P0 - (BMRF*(P0 - Pmin) |
BMR Factor
User defined value that is used to derive the BMR; serves as the basis for BMD and BMDL.
Constant Variance
If selected (Default) a constant variance is assumed for each dose group. If not selected, variance is modeled, and can differ for each dose group.
Degree Poly
Polynomial degrees should not exceed the number of dose groups unless beta coefficients are restricted.
Like dichotomous models, includes model version number, date and time, input data, form of response function, model option choices, initial parameter values, parameter estimates, asymptotic correlation matrix of parameter estimates, result summary (BMDs & BMDLs).
In addition, Likelihood and AIC values are derived for each of five models:
| "Full" Model A1: | Yij = Mu(i) + e(ij), Var{e(ij)} = Sigma^2 |
| "Fullest" Model A2: | Yij = Mu(i) + e(ij), Var{e(ij)} = Sigma(i)^2 |
| "Fullest" Model A3: | Yij=Mu(i)+e(ij), Var{e(ij)}=alpha*(Mu(i))^rho |
| "Fullest" Model A3: | Yij=Mu(i)+e(ij), Var{e(ij)}=alpha*(Mu(i))^rho |
| "Reduced" Model R: | Yi = Mu + e(i), Var{e(i)} = Sigma^2 |
| "Fitted" Model: | The user specified model. |
Model Likelihood ratios can be used to compare models because as sample size & number of dose groups increase, -2*log (likelihood ratio) converges to a Chi-square random variable, which can be used to obtain approximate probabilities to make decisions about model fit. Depending on whether variance is modeled or not, BMDS performs 3 or 4 tests for each model run.
Sessions are used to process multiple models and multiple sets of data all at once as opposed to just one model with one dataset at a time.
- Creating Sessions
A new session is created by selecting New Session or by using the toolbar icon . Alternatively an existing or previously saved session can be opend by selecting Open Session or using the toolbar icon. - Selecting Models and Parameters
- Viewing Session Output
The results are displayed after click the Run button in the session window. Results are grouped by endpoint unless otherwise specified in the Options... menu under Tools.
New Session
Open Session
Model Type
Once a session is open, a model type can be selected with the drop down box. To add additional models to the session table, select Session Grid from the main menu. The Session Grid menu allows a single row or a user determined number of rows to be added to the session table. There is also a Delete Row function.
Model Name
Right click on the row under the Model Name column. A menu will appear with a choice of models depending on the model group previously selected.
Data File
Data is stored in files with the *.dax extension. A new dataset can be created by right clicking on a field under the Data File column. Data may be created, edited or selected from an existing *.dax file.
Run?
A checkmark indicates a model will be run once Run has been clicked. An empty box indicates the model will not be run. Right-clicking will display a submenu with the options to check or uncheck all at once.
Model Option File
Right-click to select the option file and specify variable parameters. A new option file may be created or and a previously saved file may be used.
Endpoint
This column indicates how the results in the summary screen will be grouped.
Run (button)
Clicking Run will cause BMDS to compute all the models in the session with a checkmark under Run?.
Save (button)
This button will prompt you to save your new session or will save modifications to the existing session.
Close (button)
Clicking close will close the session window.
Right-click on a plot to copy it to the clipboard and paste in another program.
The models are summarized in a table format. Each lettered column corresponds to the models added in the session window. Right-clicking in a column will open a submenu with options to show the out file and graph, display array values (if right clicking on a specific array), open the data file, or open the option file associated with the model.
 Back to Previous Section |
 Forward to the Next Section |