A
absolute value of coefficient 133
Actual by Predicted leverage plot 276–278, 456
Actual by Predicted Plot table 456
Add Columns command (Cols menu) 89
Add Multiple Columns command
Cols menu 53, 55, 175
Add Rows command (Rows menu) 53, 56
Add Rows dialog box 56
aggression study
in factorial ANOVA 257–268
in MANOVA with between-subjects factor 298–300
in one-way ANOVA 227–231
R2 statistic in 230–231
alternative hypotheses
described 23
directional 24–25
nondirectional 23–25
test of association and 24–25
test of group differences and 23–24
analysis of covariance (ANCOVA) 22, 415
analysis of variance
See ANOVA (analysis of variance)
Analysis of Variance report 311–312
Analysis of Variance table
factorial ANOVA with between-subjects factor 279, 293
multiple regression analysis 456
one-way ANOVA with between-subjects factor 240–242, 248–249
Analyze menu 35, 213, 220
analyzing data
See data analysis
ANCOVA (analysis of covariance) 22, 415
annotate tool (Tools menu) 247
ANOVA (analysis of variance)
described 128–129
factorial with between-subjects factor 255–296
MANOVA similarities to 298–299
multiple regression and 412
naturally occurring variables and 415
one-way with between-subjects factor 225–254
ANOVA Summary table
factorial ANOVA with between-subjects factor 281–282, 284
mixed-design ANOVA 390
one-way ANOVA with between-subjects factor 242–243
one-way ANOVA with repeated-measures factor 336–337
approximately normal distribution 102
association, measures of
alternative hypothesis and 24–25
described 21–22, 123–124
null hypothesis and 24–25
B
bar charts
labeling 218–219, 247, 330–331
producing 204
Best data format 58
Beta weights 461–462
between-subjects designs
assumptions for 406–408
factorial ANOVA 255–296, 357–408
group effect in 389–390
MANOVA 297–320
mixed-design ANOVA and 359
one-way ANOVA 225–254
repeated-measures designs versus 228, 323, 338–342
Beveled option (Analysis of Variance table) 240
bivariate association
assumptions underlying 161–162
chi-square test of independence 148–158
choosing correct statistic 124–129
described 123–124
Fisher’s exact test 159–160
Multivariate platform 139–148, 451
Pearson correlations 130–146
Spearman correlations 146–148
table of appropriate statistics 126
bivariate correlations 451
bivariate normal distribution 161, 512
Bivariate platform
See Fit Y by X platform
C
carryover effects 341–342, 371
categorical variables
See classification variables
cause-and-effect relationships
multiple regression and 416–417
nonexperimental research and 15–16
cells in tables 149, 162
central tendency measures 86–87
character data types 57–58
Chart command (Graph menu) 204, 218, 247, 330
chi-square test of homogeneity 149
chi-square test of independence
assumptions underlying 162
computing 150–152
computing from raw data 152, 158
computing from tabular data 152–158
described 127
two-way classification tables 148–150
when to use 148
Choose Response menu
Contrast option 385–386
described 384–385
Identity option 308, 385
Repeated Measures option 345–346, 386–387, 397
Sum option 385–386
CI of Correlations option (Multivariate platform) 145
classification variables
ANOVA versus multiple regression 414
described 9
mixed-design ANOVA 359
nominal scales and 11, 124
quantitative variables versus 9
value and 8
clipboard 61
coefficient alpha
See Cronbach’s alpha
coefficient of determination 428
collinearity 440, 469
Cols menu
Add Columns command 89
Add Multiple Columns command 53, 55, 175
Column Info command 53, 56–57, 89
Delete Columns command 56, 78
described 49, 50–51
Formula option 175
New Column command 53, 55, 90, 507
Reorder Columns command 51
column formulas 59, 65–70
Column Info command (Cols menu) 53, 56–57, 89
Column Info dialog box
accessing Formula Editor 66–67
changing modeling types 125
Column Name option 69–70
Column Properties menu 59–60, 96–98, 235–236, 273, 305, 378
Data Type menu 89
described 57
Format option 69–70
Column Name option (Column Info dialog box) 69–70
Column Properties menu
described 59
Formula property 59
List Check property 60, 96–98, 235–236, 273, 305, 378
Notes property 60
Range Check property 60
Value Labels property 60
columns in tables
See also variables
assigning properties to 58–60
column names 56
concatenating tables end to end 77–79
considerations joining tables 81–82
creating and deleting 55–56
described 9–10, 51–52, 57
duplicating 56
formulas for 59, 65–70
selecting/highlighting 53–55
splitting and stacking 71–74
Columns panel (data table) 49–50, 125
comma-delimited files 62
commitment study
See investment model study
Compare Means option (Oneway Analysis title bar) 334–335, 337
component (factor) scores 504–506
Concatenate command (Tables menu) 77–79
Concatenate dialog box 77–78
concatenating tables 77–79
conclusions, drawing 7
Construct Model Effects list (Fit Model dialog box) 403
Contingency Analysis menu 159
Contingency Table (Fit Y by X platform) 155–157
contingency tables
See two-way classification tables
Continuous Fit command (Histogram title bar) 107–108
continuous modeling type 14, 57, 124–126
continuous numeric measurement 512
continuous variables
ANOVA versus multiple regression 414
distribution results for 92–93
Pearson correlation assumptions 161
contrast reports 351–353
Contrast response design 385–386
control, locus of 28
control groups
advantages of 362–364
described 18
experimental groups versus 18
interactions and 266–294, 366–367, 370–401
random assignment to 364–365
testing for simple effects 396–400
copy and paste operations 61
Copy command (Edit menu) 61
correlated predictor variables 432–441
correlated-samples t-test
See paired-samples t-test
correlation coefficient
Pearson 123–124, 128, 130–146
Spearman 127–128
testing significance of 21–22
correlation matrix
multiple regression analysis 430, 432–433
principal component analysis 474–475, 488
correlational research
See nonexperimental research
Correlations Multivariate option (Multivariate platform) 144
counterbalancing technique 341
covariance, homogeneity of
See homogeneity of covariance
Covariance Matrix option (Multivariate platform) 145
covariates 415
criterion variables
See response variables
Cronbach’s alpha
computing 169–178
described 164, 168–169
item-total correlation and 174–177
multiple-item scale and 172–174, 177–178
Multivariate platform for 164, 171–178
crosstabs report 313
csv file format 62
cumulative percent of variance accounted for 498–499
Currency numeric format 58
Customize Summary Statistics command (Summary Statistics title bar) 108
D
dat file format 62
data
See also tables
copying and pasting 61
creating subsets of 74–77
described 7
gathering 7, 447–448
managing in tables 70–83
subsets of 74–77
total variance in 479–480
data analysis
basic approaches to research 14–18
common language for 2–3
descriptive versus inferential analysis 18–20
hypothesis testing in 20–29
JMP modeling types 14
observational units in 9–10
ordering values in 272–273
scales of measurement in 10–14
steps to follow 3–7
values in 8
variables in 8–9
data files
See files
data formats for column data 58–59
data grid (JMP table) 49, 51–52
data manipulation
computing column values with formulas 65–70
copying and pasting data 61
reading data into JMP from other files 61–65
data screening concept 86
data table panels 49–51
data tables
See tables
Data Type menu 89
data types 57–58, 318
Data with Preview radio button (Open File dialog box) 63–64
Date numeric format 58
Delete Columns command (Cols menu) 56, 78
Delete Rows command (Rows menu) 56
deleting
columns 55–56
rows 56
delimited data in files 62–64
Density Ellipse option (Fit Y by X platform) 139, 143, 145
dependent variables
See also response variables
described 17
experimental research and 18
investment model study 186–187
statistics for pairs of variables 126
descriptive analysis
See also Distribution platform
described 19, 86–87
helpfulness social survey example 87–90
of population 19
descriptive statistics 331–333
differences
See nonsignificant differences
See significant differences
directional alternative hypothesis 24–25
Display Options command (Histogram title bar) 105, 108
distribution analysis
computing summary statistics 90–118
described 85–87
helpfulness social survey 87–90
outlier box plots 110–112
stem-and-leaf plots 112–117
step-by-step example 118
testing for normality 104–110
Distribution platform
changing preferences for 374–375
computing summary statistics 90–118
described 85, 91
descriptive analysis and 86–87
distribution analysis example 118
generating histograms 38–39
helpfulness social survey 87–90
mixed-design ANOVA 373–382
overlay plots 377–378, 380–382
profile plots 378
testing for normality 104–110
divide operator 68
drawing conclusions 7
E
E matrix 386
Edit menu
Copy command 61
Journal command 45
Layout command 45
Paste command 61
Effect Leverage emphasis option 275
effect size 196–197, 216–217
Effect Tests table
factorial ANOVA with between-subjects factor 275–276, 281, 288–289
multiple regression analysis 462–463
eigenvalue-one criterion 493–495
Eigenvalue table 497–498
eigenvalues
described 478, 491
scree test 495–497
Ellipsoid 3D Plot option (Multivariate platform) 145–146
emphasis types (Fit Model platform) 275, 311, 403
EMS (Expected Mean Squares) method 405–406
errors of prediction 425, 468
Exclude/Unexclude command (Rows menu) 50
Exit JMP command (Windows) 34
expected frequencies 153, 162
Expected Mean Squares (EMS) method 405–406
experimental conditions
described 18
MANOVA with between-subjects factor 305–318
one-way ANOVA with between-subjects factor 231–251
experimental groups
control groups versus 18, 362–364
described 18
interactions and 266–294, 366–367, 370–401
random assignment to 364–365
testing for simple effects 396–400
experimental research
ANOVA and 412
choosing correct statistical procedure 516–523
dependent variables and 18
described 16–18
fixed-effects models and 27–28
independent variables and 18
predictor variables and 17
response variables and 17
F
F ratio
factorial ANOVA with between-subjects factor 289–290, 293
multiple regression analysis 462–463
one-way ANOVA with repeated-measures factor 351–352
F statistic
factorial ANOVA with between-subjects factor 281, 293
MANOVA with between-subjects factor 301, 303–304, 309–310
one-way ANOVA with between-subjects factor 240–242, 248, 251–253
one-way ANOVA with repeated-measures factor 347–348, 350–351
p-values for 240–242, 248–249, 251, 309–311
understanding the meaning of 251–253
Wilks’ lambda and 301, 303–304, 309
Factor Analysis option (Principal Components title bar) 500
factor analysis versus principal component analysis 480–482
factor-based scale 506
factor-based scores 504, 506–510
Factor Profiling command (Whole Model title bar) 290
Factor Rotation report 501
factor (component) scores 504–506
factorial ANOVA with between-subjects factor
See also mixed-design ANOVA
aggression study 257–268
assumptions underlying 295–296, 406–408
described 256–257
Fit Model platform 273–275, 287–288
interpreting results 275–276, 279–286, 289–294
investment model study 268–294
possible results from 260–268
significant interaction 266–268, 287–294
summarizing analysis results 286–287, 294
with nonsignificant interaction 268–287
with nonsignificant main effects 265
with significant main effects 261–265, 281
factorial ANOVA with repeated-measures factor 406–408
factorial design studies 256–260
Fahrenheit degree scale 12
File menu
described 33
Exit JMP command 34
New command 52
Open command 32, 35, 62–64
Preferences command 375
Quit command 34
Save As command 52
files
delimited data in 62–64
importing 62
opening 63–64
reading data into JMP from other 61–65
firefighter success example 437–439
Fisher’s exact test 159–160
Fit Model dialog box
Construct Model Effects list 403
emphasis types 275, 311, 403
Model Effects area 344–345
personality types 275, 303, 306, 311, 344, 383
Run button 345, 454–455
Select Columns list 403
Fit Model platform
described 273–275
factorial ANOVA with between-subjects factor 273–275, 287–288
MANOVA with between-subjects factor 303–304, 306, 311, 316
mixed-design ANOVA 383–384, 394–395, 397
multiple regression analysis 447, 454–462, 464
overlay plots 377
profile plots 378
repeated-measures analysis 344–350, 403–405
significant main effects with 383–384
testing slices 291–294, 396–400
Fit Y by X platform
bivariate association 136, 139, 154
computing chi-square 154
computing Pearson correlations 139
computing single correlation coefficient 139–141
Contingency Table 155–157
Density Ellipse option 139, 143, 145
described 139
investment model study 135–138
Means/Anova/Pooled t option 192, 194, 202
one-way ANOVA with between-subjects factor 236–239, 248–249
one-way ANOVA with repeated-measures factor 329–337
performing t-tests in 191–198
producing scatterplots with 43, 135–138
Tests report 157–158
Fitted Normal title bar 107, 109
fixed-effects factor 27
See also independent variables
fixed-effects models
described 27
experimental research and 27–28
nonexperimental research and 28
random-effects models versus 28–29
Format option (Column Info dialog box) 69–70
formats for column data 58–59
Formula Editor 66–70, 175, 507–508
Formula option (Cols menu) 175
Formula property (Column Properties menu) 59
formulas, column 59, 65–70
frequencies
expected 153
observed 153
Full Factorial option (Macros menu) 274
full multiple regression equation 454–462
Function Browser 66
G
gathering data 7, 447–448
gender (classification variable) 9, 11
Go to Row subcommand (Row Selection dialog box) 54–55
goal-setting theory 5
Goodness-of-Fit test 107–110
Graph menu
Chart command 204, 218, 247, 330
described 35
Overlay Plot option 381
Scatterplot 3D option 487
Group button (Summary dialog box) 331, 379
group differences tests
alternative hypothesis and 23–24
described 21
example of 26
null hypothesis and 22–23
group effect in between-subjects designs 389–390
groups
See control groups
See experimental groups
H
H matrix 386
helpfulness social survey
computing summary statistics 90–118
described 87–90
Hide/Unhide command (Rows menu) 50
highlighting
histogram bars 39–42
rows and columns 53–55
histogram bars
creating subsets 76–77
highlighting 39–42
ordering 96–98
sample distributions 102–103
Histogram title bar
Continuous Fit command 107–108
Display Options command 105, 108
outlier box plots 110
histograms
creating subsets 76–77
generating 38–39
highlighting bars 39–42
Hoeffding’s D option (Multivariate platform) 145
holding constant 441
homogeneity, chi-square test of 149
homogeneity of covariance
described 342–343, 402
factorial ANOVA assumptions 407
MANOVA assumptions 319–320
Mauchey’s criterion 346–347
homogeneity of variance
factorial ANOVA assumptions 296
multiple regression assumptions 468
one-way ANOVA assumptions 254
t-test assumptions 222–223
hypotheses
alternative 23–25
described 5
developing 5–6
drawing conclusions regarding 7
null 22–23
types of 22–25
hypothesis testing
described 7, 20–21
fixed effects versus random effects 27–29
p-value 25–27
types of hypotheses 22–25
types of inferential tests 21–22
I
Identity response design 308, 385
importing data into JMP 62
independence, chi-square test of
See chi-square test of independence
independent observations
factorial ANOVA assumptions 295, 406
MANOVA assumptions 318–319
multiple regression assumptions 468
one-way ANOVA assumptions 253, 354–355
t-test assumptions 221–222
independent-samples t-test
assumptions underlying 221
described 26, 182–183
entering data into data table 189–190
interpreting results 194–198
investment model study 184–204
one-way ANOVA with between-subjects factor versus 228
performing 191–194
summarizing analysis results 198–201
with nonsignificant differences 201–204
independent variables
See also predictor variables
described 17
experimental research and 18
fixed- and random-effects models 27–29
fixed-effects factor and 27
in interactions 266, 366
investment model study 187–189
levels of 18, 27–29
main effects for 261–265
simple effects for 291–294, 396–400
inferential statistical analysis 19–22
instrument, defining 7
insurance studies 14–15
Interaction title bar 292
interactions 266, 366
See also nonsignificant interactions
See also significant interactions
intercept constant 424
internal consistency 164, 168–178
interquartile range, outlier box plots 111
interval scales
described 12–13, 124–125
modeling type and 14, 124–125
quantitative variables and 12–13
Inverse Correlations option (Multivariate platform) 145
Invert Row Selection subcommand (Row Selection dialog box) 54–55
investment model study
alternative test of 213–219
bivariate associations 135–138
dependent variable in 186–187
entering data into data table 189–190
factorial ANOVA with between-subjects factor 268–294
independent-samples t-test 184–204
independent variable in 187–189
investment size construct 325–354, 360–362
MANOVA with between-subjects factor 301–318
mixed-design ANOVA 360–401
multiple regression analysis 445–467
one-way ANOVA with between-subjects factor 231–253
one-way ANOVA with repeated-measures factor 323–325
paired-samples t-test 206–221
item-total correlations 174–177
J
JMP data
See data
JMP modeling types
See modeling types
JMP software
experimenting with 44–45
file types supported 62
JMP approach to statistics 35–36
starting JMP application 32–34
step-by-step JMP example 36–45
JMP Starter Window 33–34
JMP tables
See tables
Join command (Tables menu) 79–83
Join dialog box
Matching Specifications radio button 80–82
Select Columns For Joined Table check box 403
joining JMP tables 79–83
Journal command (Edit menu) 45
JSL scripting language 35–36
K
Kaiser-Guttman criterion 493–495
Kendall’s Tau option (Multivariate platform) 145
Kolmogorov-Smirnov-Lillefor’s (KSL) statistic 108
Kruskal-Wallis test 129
KSL (Kolmogorov-Smirnov-Lillefor’s) statistic 108
kurtosis
described 103
negative 103, 106
positive 103, 106
L
label points, generating 43–44
Label/Unlabel command (Rows menu) 37, 44, 50
labeling bars 247
Layout command (Edit menu) 45
Least Significant Difference (LSD) 243–244, 337
Least Squares means plot 284–286
least squares principle
multiple regression analysis 425–427
principal component analysis 478
leptokurtic distribution 103, 106
letter report 313
levels of measurement
described 9
factorial ANOVA assumptions 406
interval scales 12–13
MANOVA assumptions 318
modeling types and 14, 124–125
multiple regression assumptions 467
nominal scales 11
one-way ANOVA assumptions 354
ordinal scales 11–12
principal component analysis assumptions 512
quasi-interval 13
ratio scales 13–14
t-test assumptions 221–222
leverage plots 276–279, 458–459
Likert scale 165
linear combination of predictor variables 427
linear relationships between variables 133–134
linearity
multiple regression assumptions 468
Pearson correlation assumptions 161
principal component analysis assumptions 512
List Check property (Column Properties menu)
described 60
in Distribution platform 96–98, 378
in Fit Model platform 273, 305
in Fit Y by X platform 235–236
little jiffy factor analysis 500–501
locus of control 28
LSD (Least Significant Difference) 243–244, 337
M
M matrix 384–386
Macintosh environment
JMP Starter Window 33
TextEdit editor 62
Macros menu 274
magnitude of the treatment effect 230–231
main effects 261
See also nonsignificant main effects
See also significant main effects
main menu bar 33
manipulated variables 17, 414–415
Manova Fit panel 383–384
Manova personality
MANOVA with between-subjects factor 303, 306
mixed-design ANOVA 383
one-way ANOVA with repeated-measures factor 344
MANOVA Summary table 400–401
MANOVA with between-subjects factor
aggression study 298–300
assumptions underlying 318–320
described 298–300
Fit Model platform 303–304
interpreting results 309–313
investment model study 301–318
summarizing analysis results 314–318
Wilks’ lambda 301, 303–304, 309–311
with significant differences 305–316
MANOVA with repeated-measures factor 387–393
marginal totals 149
Marker Size command (scatterplots) 193
Markers command (Rows menu) 193
marriage encounter program
mixed-design ANOVA 361–401
one-way ANOVA with repeated-measures factor 326–329
Matched Pairs option (Analyze menu) 213, 220
Matched Pairs report 215
Matched Pairs title bar 214
matched-samples t-test
See paired-samples t-test
Matching Columns option (Oneway Analysis title bar) 333–334
Matching Fit report 335–336
matching procedure 207–209
Matching Specifications radio button (Join dialog box) 80–82
Mauchey’s criterion 346–347
mean (average) 19
mean square between groups 251–252
mean square within groups 252
Means/Anova option (Oneway Analysis title bar) 238
Means/Anova/Pooled t option (Fit Y by X platform) 192, 194, 202
Means Comparison report 243–245, 337
means diamond
in outlier box plots 111
t-tests and 154
Means for Oneway Anova table 249
measurement, scales of
See levels of measurement
measurement error 166, 468
measures of association
See association, measures of
Method of Moments 405
Minimal Report emphasis option 311, 403
minus operator 67
missing data
ANOVA Summary table with 282
summary statistics and 98
mixed-design ANOVA
alternative approach to 402–406
assumptions underlying 406–408
described 359–365
Fit Model platform 383–384, 394–395
interpreting results 387–392, 395–401
investment model study 360–401
marriage encounter study 361–401
possible results from 365–371
problems with 371–372
summarizing analysis results 392–393
with nonsignificant interaction 370–393
with nonsignificant main effects 370–371
with significant interaction 366–367, 393–401
with significant main effects 367–370, 383–384
mixed-effects models 28
mixed-model designs 357–408
modeling types
changing 125
described 9, 57–58
factorial ANOVA assumptions 295
JMP tables and 57–58
levels of measurement and 14, 124–125
MANOVA assumptions 318
one-way ANOVA assumptions 253
statistics for pairs of variables 126
Move Rows command (Rows menu) 51
multiple comparison procedures
described 230
factorial ANOVA with between-subjects factor 284–286
MANOVA with between-subjects factor 313
one-way ANOVA with between-subjects factor 229–230, 236–239, 243
multiple correlation coefficient (R) 427–428, 457
multiple-item scale
computing item-total correlation 174–177
Cronbach’s alpha for 172–174, 177–178
multiple operator 69
multiple regression analysis
assumptions underlying 467–469
described 411–417
estimating full multiple regression equation 454–462
Fit Model platform 447, 454–462
interpreting results 427–445, 452–454
investment model study 445–467
Multivariate platform 463–464
predicting response from multiple predictors 417–427
simple statistics and correlations 449–454
summarizing analysis results 463–467
univariate statistics for 450
multiple regression coefficient 423–425, 441–445
multiple regression equation 454–462
multivariate ANOVA for repeated-measures analysis 342–354
multivariate normality
factorial ANOVA assumptions 407
MANOVA assumptions 319
one-way ANOVA assumptions 355
Multivariate platform
bivariate association 139–148, 451
CI of Correlations option 145
computing Cronbach’s alpha 164, 171–178
computing multiple correlations for set of variables 141–144
computing Spearman correlations 147–148
Correlations Multivariate option 144
Covariance Matrix option 145
described 139
Ellipsoid 3D Plot option 145–146
Hoeffding’s D option 145
Inverse Correlations option 145
item-total correlation 174–177
Kendall’s Tau option 145
multiple regression analysis 463–464
Nonparametric Correlations option 145
other options used 143–145
Pairwise Correlations option 143, 145, 451
Partial Correlations option 145
principal component analysis 487
Spearman’s Rho option 145
multivariate test assumptions 406–407
N
N Missing statistic 98
naturally occurring variables 14, 414–415
negative correlation between variables 131
negative kurtosis 103, 106
negative skewness
described 104, 106
in outlier box plots 112
in stem-and-leaf plots 115–117
New Column command (Cols menu) 53, 55, 90, 507
New Column dialog box 55–56, 507–508
New command (File menu) 52
New Property menu 66–67
nominal modeling type
chi-square test assumptions 162
described 14, 57, 124
JMP tables and 57
statistics for pairs of variables 126
nominal scales
classification variables and 11
described 11, 124
modeling type and 14, 124
nondirectional alternative hypothesis 23–25
nonexperimental research
choosing correct statistical procedure 516–523
described 14–16
fixed-effects models and 28
predictor variables and 15
response variables and 15
nonlinear relationships between variables 133–134
nonmanipulative research
See nonexperimental research
Nonparametric Correlations option (Multivariate platform) 145
nonsignificant differences
independent-samples t-test 201–204
MANOVA with between-subjects factor 316–318
one-way ANOVA with between-subjects factor 248–251
nonsignificant interactions
factorial ANOVA with between-subjects factor 268–287
mixed-design ANOVA 370–393
nonsignificant main effects
factorial ANOVA with between-subjects factor 265
mixed-design ANOVA 370–371
nonstandardized multiple regression coefficients 442–444
normal distributions
bivariate 161, 512
departures from 100–104
factorial ANOVA assumptions 296
histogram sample 102
multiple regression assumptions 467
one-way ANOVA assumptions 254
Pearson correlation assumptions 161
principal component analysis assumptions 512
t-test assumptions 222–223
testing for 98–100, 104–110
Notepad editor 62
Notes property (Column Properties menu) 60
null hypotheses
described 22–23
p-value and 26–27, 108, 195
test of association and 24–25
test of group differences and 22–23
numeric data formats 58
numeric data types 57–58
O
observational research
See nonexperimental research
observational units 9–10
observed frequencies 153
observed variables
number of components extracted and 476, 493
optimally weighted 478
underlying constructs versus 166
Omnibus model 293
one-sided statistical tests 25
one-tailed tests
See one-sided statistical tests
one-way ANOVA with between-subjects factor
aggression study 227–231
assumptions underlying 253–254
described 227–231
Fit Y by X platform 236–239, 248–249
independent-samples t-test versus 228
interpreting results 239–245
investment model study 231–253
nonsignificant differences between experimental conditions 248–251
significant differences between experimental conditions 231–248
one-way ANOVA with repeated-measures factor
assumptions underlying 354–355
described 322–325
Fit Y by X platform 329–337
investment model study 323–354
sequence effects 341–342
single-group designs and 359–362
summarizing analysis results 338, 353–354
univariate versus multivariate analysis 342–354
weaknesses of 339–340
with significant differences 325–338
Oneway Analysis title bar
Compare Means option 334–335, 337
Matching Columns option 333–334
Means/Anova option 238
Open command (File menu) 32, 35, 62–64
Open File dialog box
Data with Preview radio button 63–64
described 48
opening JMP tables 35, 37–38
optimal weights 478–479
optimally weighted combination of predictor variables 427
order effects 340–341, 371
ordinal modeling type
chi-square test assumptions 162
described 14, 57, 124
JMP tables and 57
Spearman correlation assumptions 161
statistics for pairs of variables 126
ordinal scales
described 11–12, 124
modeling type and 14, 124
quantitative variables and 11–12
outlier box plots 110–112, 374
outliers
described 102–103
distribution examples with 108–110
histogram sample 102
Overlay Plot command (Tables menu) 378
Overlay Plot option (Graph menu) 381
Overlay Plot platform 381–382
overlay plots 377–378, 380–382
P
p-value
described 25–26, 195
for F statistic 240–242, 248–249, 251, 309–311
null hypothesis and 26–27, 108, 195
W statistic and 108, 110, 116
paired-samples t-test
assumptions underlying 222–223
described 183, 204–205
interpreting results of 215–217
investment model study 206–221
pretest-posttest studies 209, 211–212, 219–220
problems with 210–211
research design examples 205–209
summarizing analysis results 217–219
when to use 211–212
Paired t Test report 217
Pairwise Correlations option (Multivariate platform) 143, 145, 451
Parameter Estimates table
Distribution platform 107
factorial ANOVA with between-subjects factor 275
multiple regression analysis 460–462
parameters, population 19
Partial Correlations option (Multivariate platform) 145
paste (copy and paste operations) 61
Paste command (Edit menu) 61
Pearson correlation coefficient
assumptions underlying 161
characteristics of 131–133
computing 139–144
described 123–124, 128
interpreting 131–133
linear versus nonlinear relationships 133–134
other options used 144–146
producing scatterplots 135–138
when to use 130–131
person (observational unit) 9
personality types (Fit Model platform)
factorial ANOVA with between-subjects factor 275
MANOVA with between-subjects factor 303, 311
mixed-design ANOVA 383
Platforms tab (Preferences panel) 375
platykurtic distribution 103, 106
plots
See specific types of plots
POI instrument
See Prosocial Orientation Inventory instrument
population
described 18
descriptive statistical analysis of 19
parameter of 19
sample of 19, 75
positive correlation between variables 131
positive kurtosis 103, 106
positive skewness
described 104–105
in outlier box plots 112
in stem-and-leaf plots 115–117
predicted variables
See response variables
prediction errors 425, 468
predictive equation
regression coefficients and intercepts 423–425
simple 418–422
with weighted predictors 422–423
predictor variables
ANOVA versus multiple regression 414
choosing correct statistical procedure 516–523
correlated 432–441
described 15
experimental research and 17
fixed- and random-effects models 27–29
in interactions 266, 366
investment model study 190
linear combination of 427
main effects for 261–265
mixed-design ANOVA 359
naturally occurring 414–415
nonexperimental research and 15
optimally weighted combination of 427
predicting response from multiple predictors 417–427
statistics for pairs of variables 126
uniqueness indices for 440–441, 461–462
variance accounted for by 428–441
Preferences command (File menu) 375
Preferences panel 375
pretest-posttest studies 209, 211–212, 219–220
principal component analysis
assumptions underlying 512
conducting 489–511
described 472–482
factor analysis versus 480–482
Multivariate platform 487
Principal Components platform 478, 487, 490
Prosocial Orientation Inventory instrument 482–511
recoding reversed items for 509–510
Scatterplot 3D platform 487
summarizing analysis results 510–511
principal components
characteristics of 478–479
computing 476–478
described 476
extracting 490–493
optimal weights for 478
retaining based on variance accounted for 497–499
total variance in data 479–480
Principal Components platform 478, 487, 490
Principal Components report 492
Principal Components title bar
Factor Analysis option 500
Save Rotated Components option 504
Scree Plot option 496–497
principle of least squares
multiple regression analysis 425–427
principal component analysis 478
Probability numeric format 58
profile plots 378
properties, assigning to columns 58–60
prosocial behavior 412–413
Prosocial Orientation Inventory instrument
conducting principal component analysis 487–511
described 482–484
minimally adequate sample size 485
number of items per component 485
preparing 484–485
Q
q statistic 243–244
qualitative variables
See classification variables
Quantiles table 374
quantitative variables
classification variables versus 9
described 9
distribution results for 92
interval scales and 12–13
ordinal scales and 11–12
ratio scales and 13–14
value and 8
quasi-interval scales 13
Quit command (Macintosh) 34
R
R (multiple correlation coefficient) 427–428, 457
R2 statistic 230–231, 283, 300
race (classification variable) 9, 11, 124
random-effects factor 27–28, 359
See also independent variables
random-effects models 27–29
random sampling
chi-square test assumptions 162
factorial ANOVA assumptions 295, 406
MANOVA assumptions 319
multiple regression assumptions 467
one-way ANOVA assumptions 253, 355
Pearson correlation assumptions 161
principal component analysis assumptions 512
t-test assumptions 221–222
random subsets of data 75
randomization in mixed-design studies 364–365
Range Check property (Column Properties menu) 60
ranking variables 124
ratio scales
described 13–14, 125
modeling type and 14, 125
quantitative variables and 13–14
statistics for pairs of variables 126
raw data
computing chi-square values 158
described 152
nonstandardized 442
tabular versus 152
reading data into JMP from other files 61–65
recoding reversed items for principal component analysis 509–510
Reference Frame option (Matched Pairs title bar) 214
reliability coefficient 167, 173
reliability of scale
See scale reliability
REML (Restricted Maximum Likelihood) method 405–406
Reorder Columns command (Cols menu) 51
repeated-measures designs
assumptions for 406–408
between-subjects designs versus 228, 323, 338–342
described 322–325
factorial ANOVA 357–408
Fit Model platform 344–350, 403–405
MANOVA 387–393
mixed-design ANOVA and 359
one-way ANOVA 321–356
paired-samples t-test 206
sequence effects in 371–372
time effect in 390
two-group 362–364
Repeated Measures option (Choose Response menu) 345–346, 386–387, 397
Replace Table option (Sort dialog box) 71
research
basic approaches to 14–18
common language for 2–3
descriptive versus inferential analysis 18–20
hypothesis testing in 20–29
JMP modeling types 14
observational units in 9–10
refining research questions 4–5
scales of measurement in 10–14
steps to follow 3–7
values in 8
variables in 8–9
Response Specification panel
Choose Response menu 308, 384, 386–387, 397
described 306–308, 384–387
E matrix 386
H matrix 386
M matrix 384–386
Test Each Column Separately Also check box 345, 385, 387, 391
Univariate Tests Also check box 345
response variables
See also dependent variables
choosing correct statistical procedure 516–523
described 15
experimental research and 17
in interactions 266, 366
investment model study 190
mixed-design ANOVA 359
multiple regression assumptions 467
naturally occurring 414–415
nonexperimental research and 15
predicting from multiple predictors 417–427
statistics for pairs of variables 126
Restricted Maximum Likelihood (REML) method 405–406
reversed items, recoding for principal component analysis 509–510
RMSE (Root Mean Square Error) 197, 203, 278
romantic commitment study
See investment model study
Root Mean Square Error (RMSE) 197, 203, 278
Rotated Factor Loading table 501–503
Rotated Factor Pattern table 505
rotation in principal component analysis 500–503
Row Selection command (Rows menu) 54–55
Row Selection dialog box
Go to Row subcommand 54–55
Invert Row Selection subcommand 54–55
Select All Rows subcommand 54–55
Select Randomly subcommand 54–55
rows in tables
considerations joining tables 80–82
creating and deleting 56
described 9–10, 51–52, 149
selecting/highlighting 53–55
Rows menu
Add Rows command 53, 56
Delete Rows command 56
described 49–51
Exclude/Unexclude command 50
Hide/Unhide command 50
Label/Unlabel command 37, 44, 50
Markers command 193
Move Rows command 51
Row Selection command 54–55
Rows panel (data table) 49–51
Run button (Fit Model dialog box) 345, 454–455
S
sample size
for multiple regression 416
for principal component analysis 486
samples
described 19
random 75
statistic of 19
Save As command (File menu) 52
Save Rotated Components option (Principal Components title bar) 504
scale reliability
Cronbach’s alpha 164, 168–178
described 164
internal consistency 168
measurement error and 166
observed variables and 166
reliability coefficient 167
summated rating scales 165
test-retest reliability 167–168
true scores and 166
underlying constructs and 166
scales of measurement
See levels of measurement
Scatterplot 3D platform 487
Scatterplot Matrix 488–489
scatterplots
generating 43–44
Marker Size command 193
producing with Fit Y by X platform 135–138
Scree Plot option (Principal Components title bar) 496–497
scree test 495–497
Select All Rows subcommand (Row Selection dialog box) 54–55
Select Columns For Joined Table check box (Join dialog box) 81–82
Select Columns list (Fit Model dialog box) 403
Select Randomly subcommand (Row Selection dialog box) 54–55
selection bias 364–365
sequence effects
carryover effects 341–342, 371
described 340, 371–372
order effects 340–341, 371
Shapiro-Wilk (W) statistic 108, 110, 116
shortest half, outlier box plots 112
significance
See statistical significance
significant differences
MANOVA with between-subjects factor 305–316
one-way ANOVA with between-subjects factor 231–248
one-way ANOVA with repeated-measures factor 325–338
significant interactions
factorial ANOVA with between-subjects factor 266–268, 287–289
mixed-design ANOVA 366–367, 393–401
significant main effects
factorial ANOVA with between-subjects factor 261–265, 281
mixed-design ANOVA 367–370, 383–384
simple effects (testing slices) 291–294, 396–400
single-group design
extension of 359–362
problems with 327–329, 361–362
skewness
described 104–106
in outlier box plots 112
in stem-and-leaf plots 114–117
Sort command (Tables menu) 71
Sort dialog box
described 71
Replace Table option 71
sorting tables 71
space-delimited files 62
Spearman correlation coefficient
assumptions underlying 161
computing 147–148
described 127–128
when to use 146–147
Spearman’s Rho option (Multivariate platform) 145
specification errors 468–469
Specification of Repeated Measures dialog box 345–346, 386–387
sphericity (homogeneity of covariance)
described 342–343, 402
factorial ANOVA assumptions 407
MANOVA assumptions 319–320
Mauchey’s criterion 346–347
split columns 71–74
Split Columns dialog box 74
Split command (Tables menu) 72, 74
Stack Columns dialog box 73
Stack command (Tables menu) 72, 217, 402
stacked columns 71–73, 217, 402
standard error of the mean 211
Standard Least Squares personality 303, 311
standard regression coefficients 461–462
standardized multiple regression coefficients 443
statistic
choosing correct 124–129
described 19–20
statistical significance
described 123
interactions in factorial ANOVA 289–290
magnitude of the treatment effect versus 230–231
main effects in factorial ANOVA 281
variance accounted for versus 457
statistics
See also summary statistics
descriptive 331–333
for pairs of variables 126
JMP approach to 35–36
Statistics Column Name Format menu 379
Statistics menu (Summary dialog box) 330–331, 379
stem-and-leaf plots 112–117
stx file format 62
Subset command (Tables menu) 74–77
Subset dialog box 75
subsets of data
creating using histograms 76–77
creating using Subset command 74–76
Sum response design 385–386
summarizing analysis results
factorial ANOVA with between-subjects factor 286–287, 294
independent-samples t-test 198–201
MANOVA with between-subjects factor 314–318
mixed-design ANOVA 392–393
one-way ANOVA with between-subjects factor 245–247, 250–251
one-way ANOVA with repeated-measures factor 338, 353–354
paired-samples t-test 217–219
principal component analysis 510–511
Summary command (Tables menu) 331, 378–379
Summary dialog box
Group button 331, 379
Statistics Column Name Format menu 379
Statistics menu 330–331, 379
Summary of Fit table
factorial ANOVA with between-subjects factor 275–276, 278
multiple regression analysis 457
summary statistics
creating table of 331–332
departures from normality 100–104
described 90–91
distribution analysis example 118
Distribution platform 91–95, 104–110
missing data 98
ordering histogram bars 96–98
outlier box plots 110–112
stem-and-leaf plots 112–117
testing for normality 98–100, 104–110
Summary Statistics table 374–377
Summary Statistics title bar 108
summated rating scales 165
supressor variables
correlated predictor variables and 432–440
described 436–437
symmetry condition 407–408
T
t statistic 26, 194–195, 215–216
t-tests
assumptions underlying 221–223
described 182
independent-samples 26, 182–204
interpreting results 194–198
means comparisons and 243–244
paired-samples 183
performing in JMP 191–198
with nonsignificant differences 201–204
tab-delimited files 62
Table panel (data table)
described 49–50
Tables command 50
tables
See also columns in tables
See also rows in tables
assigning properties to columns 58–60
cells in 149, 162
Columns panel 49–50, 124
concatenating end to end 77–79
contingency 148–150
creating 52–56
creating subsets of data 74–77
data grid in 49, 51–52
data table panels in 49–51
data types and 57
described 52
examining 37–38
factorial data in 271–272
investment model study 189–190
joining side by side 79–83
managing data in 70–83
modeling types and 57–58
opening 35, 37–38
reading data into 61–65
reviewing for multivariate analyses 343–344
Rows panel 49–51
sorting 71
stack or split columns 71–74, 217, 402
structure of 48–52
Table panel 49–50
two-way classification 148–150, 155–157, 159–160
Tables command (Table panel) 50
Tables menu
Concatenate command 77–79
described 49
Join command 79–83
Overlay Plot command 378
Sort command 71
Split command 72, 74
Stack command 72, 217, 402
Subset command 74–77
Summary command 331, 378–379
Transpose command 378, 380–381
tabular data
computer chi-square values 152–158
described 152
raw versus 152
Test Each Column Separately Also check box (Response Specification panel) 345, 385, 387, 391
test-retest reliability 167–168
Test Slices command (Interaction title bar) 292
Test Slices report 292–293
testing for normal distribution 98–100, 104–110
testing slices (simple effects) 291–294, 396–400
tests of association
See association, measures of
Tests report (Fit Y by X platform) 157–158
Text Edit editor 62
Text Import Preview dialog box 64–65
time effect in repeated-measures designs 390
Time numeric format 58
Time report 347
times (trials) 359
Tip of the Day tips 32
Tools menu 247
total variance 479–480
Transpose command (Tables menu) 378, 380–381
treatment conditions 18, 340–342
trials (times) 359
true scores 166
true zero point 12–14
Tukey’s HSD test
factorial ANOVA with between-subjects factor 284–286
MANOVA with between-subjects factor 311–313
one-way ANOVA with between-subjects factor 236–239, 244–245
two-group repeated-measures design 362–364
two-sided statistical tests, nondirectional alternative hypotheses and 25
two-tailed tests
See two-sided statistical tests
two-way ANOVA
See factorial ANOVA with between-subjects factor
See two-way mixed-design ANOVA
two-way classification tables 148–150, 155–157, 159–160
two-way mixed-design ANOVA
alternative approach to 402–406
assumptions underlying 406–408
Fit Model platform 383–384, 394–395
interpreting results 387–392, 395–401
investment model study 360–401
marriage encounter study 361–401
possible results from 365–371
problems with 371–372
summarizing analysis results 392–393
with nonsignificant interaction 370–393
with nonsignificant main effects 370–371
with significant interaction 366–367, 393–401
with significant main effects 367–370, 383–384
txt file format 62
Type I errors 343
U
underlying constructs 166
uniqueness indices 440–441, 462–463
univariate ANOVA for repeated-measures analysis 342–354
univariate repeated-measures analysis 402–408
univariate statistics for multiple regression analysis 450
univariate test assumptions 407–408
Univariate Tests Also check box (Response Specification panel) 345
V
validating data for Range Check property 60
validity, testing for hypothesis 7
Value Labels property (Column Properties menu) 60
values
classification variables and 8
computing for columns with formulas 59, 65–70
described 8
in scales of measurement 11–14
quantitative variables and 8
statistic and 19
variable reduction procedure
See principal component analysis
variable redundancy 473–475
variables
See also specific types of variables
choosing correct statistical procedure 516–523
correlation between 131–133
data formats for 58–59
described 8, 57
relationships between 133–134
scales of measurement and 9–14
statistics for pairs of 126
variance, homogeneity of
See homogeneity of variance
variance accounted for
by correlated predictor variables 432–441
by predictor variables 428–432
cumulative percent of 498–499
retaining principal components based on 497–499
statistical significance versus 457
varimax rotation 500, 505
Venn diagrams
correlated predictor variables 434–435, 440–441
predictor variables 429, 431
W
W (Shapiro-Wilk) statistic 108, 110, 116
weighted predictors 422–424
weighted principal components 478
whiskers, outlier box plots 112
whole model reports 276–279
Whole Model table 309–311
Whole Model title bar 290
Wilks’ lambda
described 300–301
F statistic and 301, 303–304
MANOVA with between-subjects factor 301, 303–304, 309–311
Windows environment
JMP Starter Window 33–34
Notepad editor 62
X
X-variables
See predictor variables
xls file format 62
xpt file format 62
Y
Y-variables
See response variables
Z
z score form 443