Research Methods for Organizational Studies

By Donald P. Schwab | Go to book overview

Subject Index

A
Abbreviations, 226
Abstraction, 12, 28
Adjusted coefficient of determination, 258
Adjusted R2, 255, 257, 258
Affability, 58
Analysis
empirical research, 6, 9, 10
report writing, 222, 225
Analysis applications
multiple correlation and regression
formulae, 148–150
graphical representation, 135
more than two independent variables, 142–143
multiple correlation, 135–139
multiple regression, 139–142
nominal independent variables, 143–146
partial coefficients, 152–154
minal independent variables, 143–146
scores on single variable
data matrix, 150–152
formulae, 115–116
relationships between statistics, 113–114
statistical representations, 110–113
tables and graphs, 108–109
simple correlation and regression
formulae, 121–124, 127–128, 132–133
graphical representation, 119–120
nominal independent variables, 128–130
regression model, 126–127
variance explained, 124–126
Analysis of variance (ANOVA), 244, 249
And, avoiding use, 44
ANOVA, see Analysis of variance
Areas under the curve, 111–112, 163, 165
Arrow symbol, 13
Assertiveness, 63
Assessment, 41
Assignment error, 188, 189, 191, 192, 212
Attenuation, reliability, 245, 246, 247, 249
Attenuation due to unreliability, 250
Average, 110
Average Y values, 129, see also Y
Averaging out, 29

B
Bar chart, 108, 109, 113, 114, 115
Behaviorally anchored observation, 46, 47
Beta coefficients
demonstration of multicollinearity, 253, 254, 255, 256
formula for two independent variables, 149
multiple regression, 141, 142, 147, 148
partial in statistical modeling challenges, 280
Between-cases designs
design applications
experiments/quasi-experiments, 70, 71, 82
surveys/field studies, 85–86
internal validity threats, 73–74
Bias
causal challenges and design foundations, 56–57, 63
coefficients and statistical modeling, 278, 285
design foundations, 66
multiple regression, 142
problems of incomplete data, 232
surveys/field studies, 88, 89–90
Biased coefficients, 280
Biased relationships, 56, 57, 59, 67
Biasing variable, 80
Binomial probability distribution, 162, 169
Bouncing betas, 253, 258
Boundary conditions, 66, 67
Bouncing betas, 253, 258

C
Cases
construct definitions, 26
deleting and missing data, 234–235
empirical research, 5–6, 10
representativeness in statistical modeling, 282
research report writing, 220–221, 225
surveys and field studies, 85
using design for causal challenges, 63–64

-319-

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