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Introduction
t JMP fto JMP for
StatisticsStatistics
Jeff Skinner, M.S.
Biostatistics Specialist
Bioinformatics and Computational Biosciences Branch (BCBB)
NIH/NIAID/OD/OSMO/OCICB
http://bioinformatics.niaid.nih.gov
S i A @ i id ihScienceApps@niaid.nih.gov
JMP Statistical Discovery
• NIAID researchers can request JMP 8.0 for Mac or
Windows PC at http://bioinformatics niaid nih govWindows PC at http://bioinformatics.niaid.nih.gov
• Desirable combination of features:Desirable combination of features:
 Spreadsheet data tables with point-and-click user interface
 Deep statistical modeling capabilities
Edit bl d i t ti hi h lit hi Editable and interactive high quality graphics
 “Dynamic variable linking” feature helps you explore your data
 Comprehensive Design of Experiments (DOE) platform
 Free NIAID training and support: ScienceApps@niaid.nih.gov
JMP Starter Window
JMP Starter Window provides shortcuts for useful functions:• JMP Starter Window provides shortcuts for useful functions:
 Opening data tables, scripts, journals or projects
 Opening analysis platforms like Design of Experiments, modeling, etc.
 Setting user preferences for file locations, displayed output, etc.
• Tip of the Day introduces JMP features from tutorials and help menu
Five Types of JMP Files
• JMP Data Tables
 Spreadsheet files that store data scripts etc Spreadsheet files that store data, scripts, etc.
• JMP Scripts
 Text files that store JMP Script Language (JSL) codep g g ( )
• JMP Reports
 Interactive graphs and results from a statistical test
• JMP Journals
 Publishing files that store read-only data tables, url links, descriptive
figures graphs statistical test results etcfigures, graphs, statistical test results, etc.
• JMP Projects
 Collection of data tables, scripts, journals and reports, p , j p
Preferences in JMP
• General preference settings
 Show JMP Starter Window and Tip of the
Day at startupDay at startup
• Platforms preferences
 Customize the output from any statistical
analysis or graph
• File location preferencesFile location preferences
 Choose default locations for opening and
saving files in Windows
Importing Data
• MS Excel® worksheets
can be imported directlycan be imported directly
 Options for first row header,
multiple sheets, etc.
 Remember to format your dataRemember to format your data
in MS Excel® first
• Use Text Import PreviewUse Text Import Preview
option to import text files
 Options for delimited and fixed
width fileswidth files
 Preview your data columns
before import to save time
Importing from a Database
• Windows PC users can open
dBASE and MS Access files
di l f JMPdirectly from JMP
 ODBC drivers are required for
Mac users and other databases
• Open subsets of the database
files using click through menus
or specific SQL statementsor specific SQL statements
 Query specific columns or even
select rows of data matching a
set of conditions (e.g. sex = male Tip: MS Excel files can be openedset of conditions (e.g. sex male
or height < 68 inches).
 Click through windows generate
SQL statements automatically
Tip: MS Excel files can be opened
as database files to import subsets
of large files, but subsets of smaller
files are best created within JMP
JMP Data Tables
• Table, Columns and Rows menus on the left hand side of the data table
• Three places to access Columns and Rows menus:
 Columns and rows windows (LHS of the data table)
 Spreadsheet hotspots (upperleft corner of spreadsheet)
D d i JMP t l b (t f JMP i d ) Drop-down menus in JMP tool bar (top of JMP window)
JMP “Hotspots”
• JMP “Hotspots” are clickable red
triangles that provide access totriangles that provide access to
additional features in JMP
• Always check the hotspots in your
test reports to find additional tests
and figures for your analyses
• JMP hotspots make tests more
interactive and customizable
Variable Types in JMP
• Three types of variables in JMP:
 Continuous (blue triangle symbols)
 Ordinal (ordered green bar symbols)
 Nominal (unordered red bar symbols)
Ch t t t i bl l b• Character or text variables can only be
ordinal or nominal variables in JMP
• Numeric variables can be anything
• Change variable types in the column info• Change variable types in the column info
menu or by clicking symbols in the column
window (shown right)
JMP Columns (Cols) Menu
• Use the column menu to add,
delete, select (go to) or reorder, (g )
columns in the data table
• The Column Info menu allowsThe Column Info menu allows
you to define the general
attributes of your variables
• The Preselect Role menu
allows you to specify variable
attributes within the analysesattributes within the analyses
 E.g. ___ is always a response
JMP Columns (Cols) Menu
• Label / Unlabel option produces and
removes special labeling in figures for
l t d l (t b l)selected columns (tag symbol)
• Hide / Unhide removes columns from view
i th d t t bl b t d t thin the data table, but does not remove them
from analyses (blindfold symbol)
E l d /U l d t i• Exclude /Unexclude removes certain
columns from analyses, but not from the
data table (strike through symbol)
• Scroll Lock / Unlock secures the locations
of the columns in the data table
JMP Columns (Cols) Menu
• The Validation window allows you verify the values
recorded in your data table
 List Check produces a list of all text responses List Check produces a list of all text responses
 Range Check reports the min and max for numeric variables,
with a list of possible constraints to remove outliers
• The Recode window allows you to recode text and
numeric variables quickly and automatically
The Formula window allows you to create• The Formula window allows you to create
transformed variables (e.g. ln(x) ) and generate
random data from theoretical distributions
• The Standardize Attributes window allows you to
specify identical properties among many columns
JMP Rows Menu
• Add, delete, move and select rows
• Exclude/unexclude, hide/unhide and
label/unlabel options same as Cols
• Use Colors and Markers options to
identify selected rows in a graphidentify selected rows in a graph
• Powerful data management with RowPowerful data management with Row
Editor, Data Filter and Row Selection
Select Where … Option
• Click > Rows > Row Selection >
Select Where to open theSelect Where … to open the
Select Where window in JMP
• Select rows meeting multiple user-
specified conditions
 Character variable conditions
e.g. Gender = “female”
 Numeric variable inequalitiesNumeric variable inequalities
e.g. 20% < Percent Body Fat < 45%
JMP Tables Menu
• Summary option creates
table of column statistics
• Concatenate to join two
tables top-to-bottom iftable of column statistics
 E.g. mean age, etc.
• Subset option creates a
p
they share columns
• Join tables with unique
columns side by side
new table from selected
rows and columns
Sort by column values
columns side-by-side
• Update missing values
from a new table
• Sort by column values
• Stack and Split columns
to rearrange data tables
• Tabulate table stats
using drag and drop
 E g mean age etcto rearrange data tables
• Transpose rows and
columns to rotate tables
 E.g. mean age, etc.
• Missing Data Pattern
finds sampling errors
JMP Toolbar Options
• Arrow tool • Lasso tool
 Regular cursor arrow
• Help tool
 Click any JMP object and be
directed its help menus
 Select an irregularly-shaped
group of points on a graph
• Magnifier tool
 Zoom in or zoom outdirected its help menus
• Selection tool
 Select elements of a report or
journal to copy and paste
 Zoom in or zoom out
• Crosshairs tool
 Identify the location of points in
a figure or plotj py p
• Scroller tool
 Precisely scroll in your report
• Grabber tool
g p
• Annotate tool
 Add notes or captions to a figure
or report
Li t l P l t l d Grab and drag axes or other
features of a figure
• Brush tool
 Highlight points on a plot
• Line tool, Polygon tool and
Simple Shape tool
 Draw lines, polygons and simple
shapes on reports
 Highlight points on a plot
p p
JMP Graphs Menu
• Use Graph Builder for drag-and-drop
200
250
Bubble Plot of Weight by Calories Sized by Percent Body Fat
• Use Chart for pie charts and bar charts
• Use Overlay and Scatterplot 3D to
100
150
Weight
1000 1500 2000 2500 3000 3500
Calories
Circle SizeUse Overlay and Scatterplot 3D to
create customizable scatter plots
• Animate a Bubble Plot over time
Circle Size
• Animate a Bubble Plot over time
• Use Cell Plot to create “heat maps” Tree Map of Region, Adverse Event
• Use Tree Map to view relationships
among categorical variables
Anemia Erythema
Headache
Induration
Leukop
enia
Malaise Nause
a
Pain Papule
Swelling
Anemia
Ecchymosis
Leukop
enia
Malaise Nodule
Pain Swelling
Anemia Headach
e
Indur
ation
Papule
Anemia
Ecchymosi
s
Erythema
Headach
e
Leukope
nia
Malai
se
Mylagia
Tenderness
Anem
ia
Arthralgia
Dimpling Headach
Myalgia Nausea
Midwest
Northwest Southeast
Southwest
among categorical variables Elavat
ed CH
50
Erythema
Pain Swelling
Tenderness
e
Induratio
n
Leukope
nia
Pain Swell
ing
TendernessNortheast
Southwest
JMP Analyze Menu
• Distribution procedure
 Collect descriptive statistics, create
histograms and run hypothesis tests
• Modeling procedures
 Nonlinear procedures for curve fitting
P titi f d t l tihistograms and run hypothesis tests
on individual variables
• Fit Y by X procedure
 Automatically fits the appropriate
relationship between two variables
 Partition for data exploration
 Neural nets and time series models
 Categorical platform for log-linear
models and share charts (JMP 7.0)
 Gaussian processes and screeningrelationship between two variables
 Simple linear regression, one-way
ANOVA, logistic regression and chi-
square tests for table data
• Matched pairs procedure
 Gaussian processes and screening
platforms (JMP 7.0)
• Multivariate procedures
 Correlations, PCA, clustering,
discriminant analysis item analysis• Matched pairs procedure
 Paired t-tests and related figures
• Fit model procedure
 Used to fit more complicated models
discriminant analysis, item analysis
and partial least squares (PLS)
• Survival and Reliability
 Kaplan-Meier and log-rank testsp
with multiple factors, etc.
 Includes general linear models (OLS),
stepwise and multivariate procedures,
generalized linear models (GLS), etc.
 Parametric survival
 Proportional hazards
 Recurrence analysis
The Distribution Platform
• Descriptive Statistics
 Moments: mean, variance, standard deviation, etc.
 Quantiles: median, interquartile range (IQR), etc
• Descriptive Figuresp g
 Histograms and boxplots
 Stem and leaf, empirical cumulative distribution
function (ecdf) and normal quantile-quantile plots
• One-sample Inferences
 Hypothesis tests for means and standard
deviationsdeviations
 Confidence, prediction and tolerance intervals
 Distribution fitting with goodness-of-fit testing
“Broadcasting” Your Hotspot
• Sometimes you want to perform several of the
same tests all at the same time
• Two options:p
 Set your platform preferences to request special tests from the
hotspot every time
 “Broadcast” your Hotspot options by control clicking any of
the individual results
• Speed up workflow and reduce “click thru”• Speed up workflow and reduce click-thru
JMP Script Features
• JMP scripting mostly for “power users” who want
to simplify processing or create new procedures
• Scripting Window also used for “SAS Integration”
to access SAS features
T h l f l f t f l• Two helpful features for casual users
 Save analyses to their respective data tables
 Leave helpful notes in data tablesLeave helpful notes in data tables
JMP Fit Y by X Platform
• Fit Y by X chooses the correct
analysis for any pair of variablesy y p
 Simple linear regression for continuous
response and predictor variables
 Logistic regression for categorical responseg g g p
and continuous predictor
 One-way ANOVA for a continuous response
and categorical predictor
 Contingency tables for categorical response
and predictor variables
30
35
40
45
50
BodyFat
Bivariate Fit of Percent Body Fat By Calories
• Fit Y by X often has both parametric
and nonparametric tests in hotspots
5
10
15
20
25
PercentB
1000 1500 2000 2500 3000 3500
Calories
JMP Fit Model Platform
• Used to fit most models with three or
more predictor variablesp
• Choose the response variables Y,
the model effects X and the model
personality to determine the model
 JMP will help guide you by providing
appropriate options for your variablesappropriate options for your variables
 Model types determined by selected
variables and model personality
 Multiple regression
 Multifactor ANOVA
 Linear mixed models
• Contact ScienceApps@niaid.nih.gov
for help building models
 Generalized linear 
models (GLIM)
 Proportional hazards 
d i i land parametric survival
Construct Model Effects
• Cross two predictors to evaluate an interaction
 I.e. synergy of fertilizer and hydration levels on plant yieldI.e. synergy of fertilizer and hydration levels on plant yield
• Nest two predictors when the levels of one
variable depend on the levels of anothervariable depend on the levels of another
 I.e. auto make and model effects (e.g. Ford Mustang)
• Choose the Random effect attribute when
factor levels represent a random sample from
the larger populationthe larger population
 E.g. Hospital and subject are random effects drawn from
populations of all possible hospitals and patients
Model Personalities
• Standard Least Squares used for most ANOVA and
regression models with continuous response variables
• Use Stepwise personality for model selection
• Use MANOVA for multivariate response variables
• Nominal or Ordinal Logistic for categorical responses
Use Generalized linear models to test for overdispersion• Use Generalized linear models to test for overdispersion
effects in least squares, logistic or log-linear models
SAS Integration
• Use JMP to access procedures
from a SAS license
 E.g. NLMixed, GLIMMIX, etc.
• Click > File > SAS > Server• Click > File > SAS > Server
connections to access a SAS
license on the local machine or
on a remote serveron a remote server
• Submit SAS code directly fromSubmit SAS code directly from
a JSL script window
JMP DOE Menu
• Design of Experiments (DOE) Platform in
JMP allows you to utilize statistics conceptsy p
while planning your experiments
 Estimate power and necessary sample sizes
 Plan efficient experiments intended to find important effects Plan efficient experiments intended to find important effects
or optimize responses
• Designed Experiments in JMP presentations
are available for any who are interested
Thank You
For questions or comments please contact:
ScienceApps@niaid.nih.gov
301.496.4455
29

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Intro to JMP for statistics

  • 1. Introduction t JMP fto JMP for StatisticsStatistics Jeff Skinner, M.S. Biostatistics Specialist Bioinformatics and Computational Biosciences Branch (BCBB) NIH/NIAID/OD/OSMO/OCICB http://bioinformatics.niaid.nih.gov S i A @ i id ihScienceApps@niaid.nih.gov
  • 2. JMP Statistical Discovery • NIAID researchers can request JMP 8.0 for Mac or Windows PC at http://bioinformatics niaid nih govWindows PC at http://bioinformatics.niaid.nih.gov • Desirable combination of features:Desirable combination of features:  Spreadsheet data tables with point-and-click user interface  Deep statistical modeling capabilities Edit bl d i t ti hi h lit hi Editable and interactive high quality graphics  “Dynamic variable linking” feature helps you explore your data  Comprehensive Design of Experiments (DOE) platform  Free NIAID training and support: ScienceApps@niaid.nih.gov
  • 3. JMP Starter Window JMP Starter Window provides shortcuts for useful functions:• JMP Starter Window provides shortcuts for useful functions:  Opening data tables, scripts, journals or projects  Opening analysis platforms like Design of Experiments, modeling, etc.  Setting user preferences for file locations, displayed output, etc. • Tip of the Day introduces JMP features from tutorials and help menu
  • 4. Five Types of JMP Files • JMP Data Tables  Spreadsheet files that store data scripts etc Spreadsheet files that store data, scripts, etc. • JMP Scripts  Text files that store JMP Script Language (JSL) codep g g ( ) • JMP Reports  Interactive graphs and results from a statistical test • JMP Journals  Publishing files that store read-only data tables, url links, descriptive figures graphs statistical test results etcfigures, graphs, statistical test results, etc. • JMP Projects  Collection of data tables, scripts, journals and reports, p , j p
  • 5. Preferences in JMP • General preference settings  Show JMP Starter Window and Tip of the Day at startupDay at startup • Platforms preferences  Customize the output from any statistical analysis or graph • File location preferencesFile location preferences  Choose default locations for opening and saving files in Windows
  • 6. Importing Data • MS Excel® worksheets can be imported directlycan be imported directly  Options for first row header, multiple sheets, etc.  Remember to format your dataRemember to format your data in MS Excel® first • Use Text Import PreviewUse Text Import Preview option to import text files  Options for delimited and fixed width fileswidth files  Preview your data columns before import to save time
  • 7. Importing from a Database • Windows PC users can open dBASE and MS Access files di l f JMPdirectly from JMP  ODBC drivers are required for Mac users and other databases • Open subsets of the database files using click through menus or specific SQL statementsor specific SQL statements  Query specific columns or even select rows of data matching a set of conditions (e.g. sex = male Tip: MS Excel files can be openedset of conditions (e.g. sex male or height < 68 inches).  Click through windows generate SQL statements automatically Tip: MS Excel files can be opened as database files to import subsets of large files, but subsets of smaller files are best created within JMP
  • 8. JMP Data Tables • Table, Columns and Rows menus on the left hand side of the data table • Three places to access Columns and Rows menus:  Columns and rows windows (LHS of the data table)  Spreadsheet hotspots (upperleft corner of spreadsheet) D d i JMP t l b (t f JMP i d ) Drop-down menus in JMP tool bar (top of JMP window)
  • 9. JMP “Hotspots” • JMP “Hotspots” are clickable red triangles that provide access totriangles that provide access to additional features in JMP • Always check the hotspots in your test reports to find additional tests and figures for your analyses • JMP hotspots make tests more interactive and customizable
  • 10. Variable Types in JMP • Three types of variables in JMP:  Continuous (blue triangle symbols)  Ordinal (ordered green bar symbols)  Nominal (unordered red bar symbols) Ch t t t i bl l b• Character or text variables can only be ordinal or nominal variables in JMP • Numeric variables can be anything • Change variable types in the column info• Change variable types in the column info menu or by clicking symbols in the column window (shown right)
  • 11. JMP Columns (Cols) Menu • Use the column menu to add, delete, select (go to) or reorder, (g ) columns in the data table • The Column Info menu allowsThe Column Info menu allows you to define the general attributes of your variables • The Preselect Role menu allows you to specify variable attributes within the analysesattributes within the analyses  E.g. ___ is always a response
  • 12. JMP Columns (Cols) Menu • Label / Unlabel option produces and removes special labeling in figures for l t d l (t b l)selected columns (tag symbol) • Hide / Unhide removes columns from view i th d t t bl b t d t thin the data table, but does not remove them from analyses (blindfold symbol) E l d /U l d t i• Exclude /Unexclude removes certain columns from analyses, but not from the data table (strike through symbol) • Scroll Lock / Unlock secures the locations of the columns in the data table
  • 13. JMP Columns (Cols) Menu • The Validation window allows you verify the values recorded in your data table  List Check produces a list of all text responses List Check produces a list of all text responses  Range Check reports the min and max for numeric variables, with a list of possible constraints to remove outliers • The Recode window allows you to recode text and numeric variables quickly and automatically The Formula window allows you to create• The Formula window allows you to create transformed variables (e.g. ln(x) ) and generate random data from theoretical distributions • The Standardize Attributes window allows you to specify identical properties among many columns
  • 14. JMP Rows Menu • Add, delete, move and select rows • Exclude/unexclude, hide/unhide and label/unlabel options same as Cols • Use Colors and Markers options to identify selected rows in a graphidentify selected rows in a graph • Powerful data management with RowPowerful data management with Row Editor, Data Filter and Row Selection
  • 15. Select Where … Option • Click > Rows > Row Selection > Select Where to open theSelect Where … to open the Select Where window in JMP • Select rows meeting multiple user- specified conditions  Character variable conditions e.g. Gender = “female”  Numeric variable inequalitiesNumeric variable inequalities e.g. 20% < Percent Body Fat < 45%
  • 16. JMP Tables Menu • Summary option creates table of column statistics • Concatenate to join two tables top-to-bottom iftable of column statistics  E.g. mean age, etc. • Subset option creates a p they share columns • Join tables with unique columns side by side new table from selected rows and columns Sort by column values columns side-by-side • Update missing values from a new table • Sort by column values • Stack and Split columns to rearrange data tables • Tabulate table stats using drag and drop  E g mean age etcto rearrange data tables • Transpose rows and columns to rotate tables  E.g. mean age, etc. • Missing Data Pattern finds sampling errors
  • 17. JMP Toolbar Options • Arrow tool • Lasso tool  Regular cursor arrow • Help tool  Click any JMP object and be directed its help menus  Select an irregularly-shaped group of points on a graph • Magnifier tool  Zoom in or zoom outdirected its help menus • Selection tool  Select elements of a report or journal to copy and paste  Zoom in or zoom out • Crosshairs tool  Identify the location of points in a figure or plotj py p • Scroller tool  Precisely scroll in your report • Grabber tool g p • Annotate tool  Add notes or captions to a figure or report Li t l P l t l d Grab and drag axes or other features of a figure • Brush tool  Highlight points on a plot • Line tool, Polygon tool and Simple Shape tool  Draw lines, polygons and simple shapes on reports  Highlight points on a plot p p
  • 18. JMP Graphs Menu • Use Graph Builder for drag-and-drop 200 250 Bubble Plot of Weight by Calories Sized by Percent Body Fat • Use Chart for pie charts and bar charts • Use Overlay and Scatterplot 3D to 100 150 Weight 1000 1500 2000 2500 3000 3500 Calories Circle SizeUse Overlay and Scatterplot 3D to create customizable scatter plots • Animate a Bubble Plot over time Circle Size • Animate a Bubble Plot over time • Use Cell Plot to create “heat maps” Tree Map of Region, Adverse Event • Use Tree Map to view relationships among categorical variables Anemia Erythema Headache Induration Leukop enia Malaise Nause a Pain Papule Swelling Anemia Ecchymosis Leukop enia Malaise Nodule Pain Swelling Anemia Headach e Indur ation Papule Anemia Ecchymosi s Erythema Headach e Leukope nia Malai se Mylagia Tenderness Anem ia Arthralgia Dimpling Headach Myalgia Nausea Midwest Northwest Southeast Southwest among categorical variables Elavat ed CH 50 Erythema Pain Swelling Tenderness e Induratio n Leukope nia Pain Swell ing TendernessNortheast Southwest
  • 19. JMP Analyze Menu • Distribution procedure  Collect descriptive statistics, create histograms and run hypothesis tests • Modeling procedures  Nonlinear procedures for curve fitting P titi f d t l tihistograms and run hypothesis tests on individual variables • Fit Y by X procedure  Automatically fits the appropriate relationship between two variables  Partition for data exploration  Neural nets and time series models  Categorical platform for log-linear models and share charts (JMP 7.0)  Gaussian processes and screeningrelationship between two variables  Simple linear regression, one-way ANOVA, logistic regression and chi- square tests for table data • Matched pairs procedure  Gaussian processes and screening platforms (JMP 7.0) • Multivariate procedures  Correlations, PCA, clustering, discriminant analysis item analysis• Matched pairs procedure  Paired t-tests and related figures • Fit model procedure  Used to fit more complicated models discriminant analysis, item analysis and partial least squares (PLS) • Survival and Reliability  Kaplan-Meier and log-rank testsp with multiple factors, etc.  Includes general linear models (OLS), stepwise and multivariate procedures, generalized linear models (GLS), etc.  Parametric survival  Proportional hazards  Recurrence analysis
  • 20. The Distribution Platform • Descriptive Statistics  Moments: mean, variance, standard deviation, etc.  Quantiles: median, interquartile range (IQR), etc • Descriptive Figuresp g  Histograms and boxplots  Stem and leaf, empirical cumulative distribution function (ecdf) and normal quantile-quantile plots • One-sample Inferences  Hypothesis tests for means and standard deviationsdeviations  Confidence, prediction and tolerance intervals  Distribution fitting with goodness-of-fit testing
  • 21. “Broadcasting” Your Hotspot • Sometimes you want to perform several of the same tests all at the same time • Two options:p  Set your platform preferences to request special tests from the hotspot every time  “Broadcast” your Hotspot options by control clicking any of the individual results • Speed up workflow and reduce “click thru”• Speed up workflow and reduce click-thru
  • 22. JMP Script Features • JMP scripting mostly for “power users” who want to simplify processing or create new procedures • Scripting Window also used for “SAS Integration” to access SAS features T h l f l f t f l• Two helpful features for casual users  Save analyses to their respective data tables  Leave helpful notes in data tablesLeave helpful notes in data tables
  • 23. JMP Fit Y by X Platform • Fit Y by X chooses the correct analysis for any pair of variablesy y p  Simple linear regression for continuous response and predictor variables  Logistic regression for categorical responseg g g p and continuous predictor  One-way ANOVA for a continuous response and categorical predictor  Contingency tables for categorical response and predictor variables 30 35 40 45 50 BodyFat Bivariate Fit of Percent Body Fat By Calories • Fit Y by X often has both parametric and nonparametric tests in hotspots 5 10 15 20 25 PercentB 1000 1500 2000 2500 3000 3500 Calories
  • 24. JMP Fit Model Platform • Used to fit most models with three or more predictor variablesp • Choose the response variables Y, the model effects X and the model personality to determine the model  JMP will help guide you by providing appropriate options for your variablesappropriate options for your variables  Model types determined by selected variables and model personality  Multiple regression  Multifactor ANOVA  Linear mixed models • Contact ScienceApps@niaid.nih.gov for help building models  Generalized linear  models (GLIM)  Proportional hazards  d i i land parametric survival
  • 25. Construct Model Effects • Cross two predictors to evaluate an interaction  I.e. synergy of fertilizer and hydration levels on plant yieldI.e. synergy of fertilizer and hydration levels on plant yield • Nest two predictors when the levels of one variable depend on the levels of anothervariable depend on the levels of another  I.e. auto make and model effects (e.g. Ford Mustang) • Choose the Random effect attribute when factor levels represent a random sample from the larger populationthe larger population  E.g. Hospital and subject are random effects drawn from populations of all possible hospitals and patients
  • 26. Model Personalities • Standard Least Squares used for most ANOVA and regression models with continuous response variables • Use Stepwise personality for model selection • Use MANOVA for multivariate response variables • Nominal or Ordinal Logistic for categorical responses Use Generalized linear models to test for overdispersion• Use Generalized linear models to test for overdispersion effects in least squares, logistic or log-linear models
  • 27. SAS Integration • Use JMP to access procedures from a SAS license  E.g. NLMixed, GLIMMIX, etc. • Click > File > SAS > Server• Click > File > SAS > Server connections to access a SAS license on the local machine or on a remote serveron a remote server • Submit SAS code directly fromSubmit SAS code directly from a JSL script window
  • 28. JMP DOE Menu • Design of Experiments (DOE) Platform in JMP allows you to utilize statistics conceptsy p while planning your experiments  Estimate power and necessary sample sizes  Plan efficient experiments intended to find important effects Plan efficient experiments intended to find important effects or optimize responses • Designed Experiments in JMP presentations are available for any who are interested
  • 29. Thank You For questions or comments please contact: ScienceApps@niaid.nih.gov 301.496.4455 29