chi3scen1 {chi2x3way} R Documentation

## Pearson's index for three-way contingency tables under Scenario 1 (prescribed probabilities)

### Description

It provides the Pearson's index, e.g. chi-square index, partitioning under the Scenario 1 when probabilities are homogeneous.

### Usage

```chi3scen1(X, pi=rep(1/dim(X)[],dim(X)[]), pj=rep(1/dim(X)[],dim(X)[]),
pk=rep(1/dim(X)[],dim(X)[]), digits = 3)
```

### Arguments

 `X` The three-way contingency table. `pi` The input parameter for specifying the theoretical probabilities of rows categories. When `scen = 1`, they can be prescribed by the analyst. By default, they are set equal among the categories, homogeneous margins (uniform probabilities), that is `pi = rep(1/dim(X)[],dim(X)[])`. `pj` The input parameter for specifying the theoretical probabilities of columns categories. When `scen = 1`, they can be prescribed by the analyst. By default, they are set equal among the categories, homogeneous margins (uniform probabilities), that is `pj = rep(1/dim(X)[],dim(X)[])`. `pk` The input parameter for specifying the theoretical probabilities of tube categories. When `scen = 1`, they can be prescribed by the analyst. By default, they are set equal among the categories, homogeneous margins (uniform probabilities), that is `pk = rep(1/dim(X)[],dim(X)[])`. `digits` The minimum number of decimal places, `digits`, used for displaying the numerical summaries of the analysis. By default, `digits = 3`.

### Value

Description of the output returned

 `z` The chi-square index partition under Scenario 1, we get seven terms of the chi-square partition, three main terms, two bivariate terms and a trivariate term. The output is in a matrix, the four rows of this matrix indicate the index, the percentage of the explained inertia, the degree of freedom, the p-value, respectively.

### Note

This function belongs to the class `chi3class`.

### Author(s)

Lombardo R and Takane Y

### References

Beh EJ and Lombardo R (2014) Correspondence Analysis: Theory, Practice and New Strategies. John Wiley & Sons.
Carlier A Kroonenberg PM (1996) Biplots and decompositions in two-way and three-way correspondence analysis. Psychometrika, 61, 355-373.
Lancaster H O (1951) Complex contingency tables treated by the partition of the chi-square. Journal of Royal Statistical Society, Series B, 13, 242-249.
Loisel S and Takane Y (2016) Partitions of Pearson's chi-square ststistic for frequency tables: A comprehensive account. Computational Statistics, 31, 1429-1452.

### Examples

```##---- Should be DIRECTLY executable !! ----
data(olive)
chi3scen1(olive)
```

[Package chi2x3way version 1.1 Index]