A data frame containing 10 variables with 47 observations.

`Russett`

A data frame containing the following variables for 47 countries:

`gini`

The Gini index of concentration

`farm`

The percentage of landholders who collectively occupy one-half of all the agricultural land (starting with the farmers with the smallest plots of land and working toward the largest)

`rent`

The percentage of the total number of farms that rent all their land. Transformation: ln (x + 1)

`gnpr`

The 1955 gross national product per capita in U.S. dollars. Transformation: ln (x)

`labo`

The percentage of the labor force employed in agriculture. Transformation: ln (x)

`inst`

Instability of personnel based on the term of office of the chief executive. Transformation: exp (x - 16.3)

`ecks`

The total number of politically motivated violent incidents, from plots to protracted guerrilla warfare. Transformation: ln (x + 1)

`deat`

The number of people killed as a result of internal group violence per 1,000,000 people. Transformation: ln (x + 1)

`stab`

One if the country has a stable democracy, and zero otherwise

`dict`

One if the country experiences a dictatorship, and zero otherwise

From: Henseler (2021)

The dataset was initially compiled by Russett (1964) , discussed and reprinted by Gifi (1990) , and partially transformed by Tenenhaus and Tenenhaus (2011) . It is also used in Henseler (2021) for demonstration purposes.

Gifi A (1990).
*Nonlinear multivariate analysis*.
Wiley.

Henseler J (2021).
*Composite-Based Structural Equation Modeling: Analyzing Latent and Emergent Variables*.
Guilford Press, New York.

Russett BM (1964).
“Inequality and Instability: The Relation of Land Tenure to Politics.”
*World Politics*, **16**(3), 442--454.
doi:10.2307/2009581
.

Tenenhaus A, Tenenhaus M (2011).
“Regularized generalized canonical correlation analysis.”
*Psychometrika*, **76**(2), 257--284.

```
#============================================================================
# Example is taken from Henseler (2020)
#============================================================================
model_Russett="
# Composite model
AgrIneq <~ gini + farm + rent
IndDev <~ gnpr + labo
PolInst <~ inst + ecks + deat + stab + dict
# Structural model
PolInst ~ AgrIneq + IndDev
"
out <- csem(.data = Russett, .model = model_Russett,
.PLS_weight_scheme_inner = 'factorial',
.tolerance = 1e-06
)
```