Observed Variable



Download 260.92 Kb.
Page2/3
Date conversion28.01.2017
Size260.92 Kb.
1   2   3

Endogenous variable (En ~~ In)

A variable whose values are explained within the theory with which we’re working. We account for all variation in the values of endogenous variables using the constructs of whatever theory we’re working with. Causes of endogenous variables originate within the model.

Basic EFA, CFA, SEM Path Analytic Notation
Observed variables are symbolized by squares or rectangles.

103

84

121



76

. . .


97

81

Observed

Variable



Latent Variables are symbolized by Circles or ellipses.

106


78

115


80

. . .


93

83

Latent



Variable

Values of individuals on latent variables are not observable, hence the dimmed text.


Correlations or covariances between variables are represented by double-headed arrows.




"Cor / Cov"

Arrow
Observed

Variable B

"Cor / Cov"

Arrow

Observed


Variable A

103


84

121


76

. . .


97

81

101



90

128


72

. . .


93

80


Latent

Variable B



Latent

Variable A



106


78

115


80

. . .


93

83
104

79

114


79

. . .


92

81

"Causal" or "Predictive" or “Regression” relationships between variables are represented by single-headed arrows


Latent

Variable


Observed

Variable


"Causal"

Arrow


Latent

Variable


Observed

Variable


"Causal"

Arrow
Latent

Variable


"Causal"

Arrow
Latent

Variable
"Causal"

Arrow


Observed

Variable


Observed

Variable
Exogenous Observed Variables




"Correlation"

Arrow





Observed

Variable


"Causal"

Arrow





Observed

Variable

Exogenous variable connect to other variables in the model through either a “causal” arrow or a correlation

Exogenous Latent Variables




"Correlation"

Arrow


Latent


Variable

"Causal"


Arrow

Latent


Variable

Exogenous latent variables also connect to other variables in the model through either a “causal” arrow or a correlation


Endogenous Observed Variables - Endogenous Latent Variable

Random


error

Random

error





Observed

Variable



Latent

Variable

"Causal"

Arrow


"Causal"

Arrow


Endogenous variables connect to other variables in the model by being on the “receiving” end of one or more “causal” arrows. Specifically, endogenous variables are typically represented as being “caused” by 1) other variables in the theory and 2) random error. Thus, 100% of the variation in every endogenous variable is accounted for by either other variables in the model or random error. This means that random error is an exogenous latent variable in SEM diagrams. Random error is a catch-all concept representing all “other” things that are affecting the endogenous variable.
Summary statistics associated with symbols


Mean, Variance

Mean, Variance




Observed

Variable


Latent


Variable

Our SEM program, Amos, prints means and variances above and to the right. Typically the mean and variance of latent variables are fixed at 0 and 1 respectively, although there are exceptions to this in advanced applications.

"Correlation"

Arrow


r or Covariance
"Causal"

Arrow


B or 

Path Diagrams of Analyses We’ve Done Previously


Following is how some of the analyses we’ve performed previously would be represented using path diagrams.
1. Simple correlation between two observed variables.
GRE-V
GRE-Q

rVQ




2. Simple correlations between three observed variables.
GRE-V
GRE-Q
GRE-A

rVQ

rQA

rVA



3. Simple regression of an observed dependent variable onto one observed independent variable.


Note that the endogenous variable is caused in part by catch-all influences.

Note that the endogenous variable is caused in part by catch-all influences.

GRE-Q
P511G

e

B or 



4. Multiple Regression of an observed dependent variable onto three observed independent variables.

GRE-V





BV or V


P511G

GRE-Q




BQ or Q
e

UPGA





BU or U


1   2   3


The database is protected by copyright ©ininet.org 2016
send message

    Main page