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For square contingency tables with ordered categories, an index based on Cressie and Read's power divergence (or Patil and Taillie's diversity index) has been proposed in order to measure the degree of departure from symmetry. Although there are two types of maximum asymmetry (i.e., whether (1) all the observations concentrate in the top-right cell in the table, or (2) they concentrate in the bottom-left cell), the existing index cannot distinguish the two directions of maximum asymmetry. This paper proposes a directional index based on an arc-cosine function in order to simultaneously represent the degree and directionality of asymmetry. The proposed index would be useful for comparing degrees of asymmetry for several square contingency tables. Numerical examples show the utility of the proposed index using some datasets. We evaluate the usefulness of the proposed index by applying it to real data of the clinical study. The proposed index provides analysis results that are easier to interpret than the existing index.

In square contingency table analysis, we consider a partial measure that represents the degree of departure from symmetry for each of several pairs. It may be useful to pool the values of the measure into a single summary measure of partial asymmetry. We show that the estimator of partial measures is asymptotically mutually independent for a large sample size. The present paper proposes a symmetry measure in the class of weighted averages that is different from previous studies. The proposed measure is an approximation of the measure in the class of weighted averages that has the smallest variance.

When focusing on changes in political party support, it is crucial to determine whether or not there has been a change in the aggregate. From this perspective, various types of marginal homogeneity models have been proposed. We propose local marginal homogeneity models, which indicate that there are symmetric structures of probabilities for only one pair of symmetric marginal probabilities or cumulative probabilities. In addition, we propose two measures, one for nominal categories and one for ordered categories, to express the degree of departure from local marginal homogeneity models. We also apply the measures to data and confirm that the measures help compare the degree of departure from the model in several tables.

For square contingency tables with ordered categories, Tomizawa, Biometrica J. 28 (1986), 387–393, considered the conditional point symmetry model. Kurakami et al., J. Stat. Adv. Theory Appl. 17 (2017), 33–42, considered the another point symmetry and the reverse global symmetry model. The present paper proposes Kullback–Leibler information type measures to represent the degree of departure from each of the models. Also this paper shows a theorem that the measure for the another point symmetry model is equal to the sum of the measures for the reverse global symmetry model and for the conditional point symmetry model.

For square contingency tables with ordered categories, there would be some situations that one would like to analyze them by using collapsed 3×3 tables combining some adjacent categories in the original table. This paper considers the marginal homogeneity for collapsed tables and proposes a measure which represents the degree of departure from the marginal homogeneity. The proposed measure lies between 0 and 1, and it takes zero when the marginal homogeneity holds. Examples are given.

For multi-way contingency table, Bhapkar and Darroch (1990) considered the marginal symmetry model for order h. The present paper proposes a marginal cumulative logistic model for order h. When h=1, this model reduces to the marginal logistic model (Agresti, 2002). It also gives a theorem that the marginal symmetry model for order h holds if and only if (i) the marginal cumulative logistic model for order h, (ii) the marginal moment equality model for order h, and (iii) the marginal symmetry model for order h-1 hold. A special case of this theorem with h=1 is identical to the result of Tahata, Katakura and Tomizawa (2007).

The double symmetry model satisfies both the symmetry and point symmetry models simultaneously. To measure the degree of deviation from the double symmetry model, a two-dimensional index that can concurrently measure the degree of deviation from symmetry and point symmetry is considered. This two-dimensional index is constructed by combining two existing indexes. Although the existing indexes are constructed using power divergence, the existing two-dimensional index that can concurrently measure both symmetries is constructed using only Kullback-Leibler information, which is a special case of power divergence. Previous studies note the importance of using several indexes of divergence to compare the degrees of deviation from a model for several square contingency tables. This study, therefore, proposes a two-dimensional index based on power divergence in order to measure deviation from double symmetry for square contingency tables. Numerical examples show the utility of the proposed two-dimensional index using two datasets.

For the analysis of square contingency tables with ordered categories, a measure was developed to represent the degree of departure from the conditional symmetry model in which there is an asymmetric structure of the cell probabilities with respect to the main diagonal of the table. The present paper proposes a novel measure for the departure from conditional symmetry based on the cumulative probabilities from the corners of the square table. In a given example, the proposed measure is applied to Japanese occupational status data, and the interpretation of the proposed measure is illustrated as the departure from a proportional structure of social mobility.

In the analysis of two-way contingency tables, the degree of departure from independence is measured using measures of association between row and column variables (e.g., Yule’s coefficients of association and of colligation, Cramér’s coefficient, and Goodman and Kruskal’s coefficient). On the other hand, in the analysis of square contingency tables with the same row and column classifications, we are interested in measuring the degree of departure from symmetry rather than independence. Over past years, many studies have proposed various types of indexes based on their power divergence (or diversity index) to represent the degree of departure from symmetry. This study proposes a two-dimensional index to measure the degree of departure from symmetry in terms of the log odds of each symmetric cell with respect to the main diagonal of the table. By measuring the degree of departure from symmetry in terms of the log odds of each symmetric cell, the analysis results are easier to interpret than existing indexes. Numerical experiments show the utility of the proposed two-dimensional index. We show the usefulness of the proposed two-dimensional index by using real data.

For two-way contingency tables, Tomizawa (1985) considered the point-symmetry and marginal point-symmetry models, and Tomizawa, Yamamoto and Tahata (2007) proposed a measure to represent the degree of departure from point-symmetry. The present paper proposes a measure to represent the degree of departure from marginal pointsymmetry for two-way tables. The proposed measure is expressed by using Cressie-Read power-divergence or Patil-Taillie diversity index. This measure would be useful for comparing the degrees of departure from marginal point-symmetry in several tables. The relationship between the degree of departure from marginal point-symmetry and the measure is shown when it is reasonable to assume underlying bivariate normal distribution. Examples are shown.

For square contingency tables with ordered categories, the present paper proposes an asymmetry model with m-additional parameters, which indicates (1) the generalized marginal homogeneity and (2) the structure of quasi-symmetry for cumulative probabilities. The proposed model includes a modified palindromic symmetry model by Iki, Oda and Tomizawa [7]. Also the present paper gives the decomposition of the symmetry model using the proposed model. Examples are given.

For square contingency tables with ordered categories, Agresti (1984, 2002) considered the marginal cumulative logistic (ML) model, which is an extension of the marginal homogeneity (MH) model. The ML model depends on the probabilities on the main diagonal of the table. This paper (1) proposes the conditional marginal cumulative logistic (CML) model which does not depend on the probabilities on the main diagonal, and (2) decomposes the MH model into the ML (CML) model and the model which indicates the equality of row and column marginal means. Examples are given.

For the analysis of square contingency tables with ordered categories, Agresti (1983) introduced the linear diagonals-parameter symmetry (LDPS) model. Tomizawa (1991) considered an extended LDPS (ELDPS) model, which has one more parameter than the LDPS model. These models are special cases of Caussinus (1965) quasi-symmetry (QS) model. Caussinus showed that the symmetry (S) model is equivalent to the QS model and the marginal homogeneity (MH) model holding simultaneously. For square tables with ordered categories, Agresti (2002, p.430) gave a decomposition for the S model into the ordinal quasi-symmetry and MH models. This paper proposes some decompositions which are different from Caussinus’ and Agresti’s decompositions. It gives (i) two kinds of decomposition theorems of the S model for two-way tables, (ii) extended models corresponding to the LDPS and ELDPS, and the generalized model further for multi-way tables, and (iii) three kinds of decomposition theorems of the S model into their models and marginal equimoment models for multi-way tables. The proposed decompositions may be useful if it is reasonable to assume the underlying multivariate normal distribution.

For the analysis of square contingency tables with ordered categories, Tomizawa et al. (2003) considered a measure to represent the degree of departure from marginal homogeneity (MH). Tomizawa (1993) considered an extended marginal homogeneity (EMH) model. This paper (i) proposes a measure to represent the degree of departure from EMH, (ii) proposes a measure from equality of marginal means (E), and (iii) gives a theorem that the value of measure for MH is equal to the sum of the value of measure for EMH and that for E.

Yamamoto, Iwashita, and Tomizawa (2007) gave the decompositions of the symmetry (S) model into the extended S and two or three marginal equimoment models for multi-way tables with ordered categories. However the goodness-of-fit test statistic for the S model is not asymptotically equivalent to the sum of those for the decomposed three or four models. This paper gives, for multi-way tables, the modification of their decompositions such that the test statistic for the S model is asymptotically equivalent to the sum of those for the extended S model and one modified marginal equimoment model, which is the constraints combined the marginal means equality and variances equality or combined the marginal means equality, variances equality and correlations equality. Examples are given.

For square contingency tables with the same row and column ordinal classifications, this paper proposes the quasi-symmetry model based on the marginal ridits. The model indicates that the log-odds that an observation will fall in the (i; j) cell instead of in the (j; i) cell, i < j, is proportional to the difference between the average ridit score of row and column marginal distributions for category j and that for category i. This paper also gives a theorem such that the symmetry model holds if and only if both the proposed model and the marginal mean equality model hold. Examples are given.

For the analysis of square contingency tables, Tomizawa (1994), Tomizawa, Seo, and Yamamoto (1998), and Tomizawa, Miyamoto, and Hatanaka (2001) considered measures to represent the degree of departure from symmetry. However, the maximum value of these measures cannot distinguish two kinds of complete asymmetry (say, complete-upper-asymmetry and complete-lower-asymmetry). The present paper proposes a measure which can distinguish two kinds of complete asymmetry for square tables with ordered categories. Especially the proposed measure is useful for representing the degree of departure from symmetry when the conditional symmetry model holds. Examples are given.

For 2 x 2 x K contingency tables, Tomizawa considered a Shannon entropy type measure to represent the degree of departure from a log-linear model of no three-factor interaction (the NOTFI model). This paper proposes a generalization of Tomizawa's measure for 2 x 2 x K tables. The measure proposed is expressed by using Patil-Taillie diversity index or Cressie-Read power-divergence. A special case of the proposed measure includes Tomizawa's measure. The proposed measure would be useful for comparing the degrees of departure from the NOTFI model in several tables.

For a T-variate density function, the present paper defines the point-symmetry, quasi-point-symmetry of order k (

For the analysis of square contingency tables, Tomizawa, Miyamoto and Ashihara (2003) considered a measure to represent the degree of departure from marginal homogeneity. However, the maximum value of this measure cannot distinguish two kinds of marginal inhomogeneity. This paper proposes a measure which can distinguish two kinds of marginal inhomogeneity for square tables with ordered categories. The measure is constructed using the arc-cosine function of symmetric cumulative probabilities. Especially the proposed measure is useful for representing the degree of departure from marginal homogeneity when the extended marginal homogeneity model holds. Examples are given.

For the analysis of square contingency tables, Tomizawa and Makii (2001), and Tomizawa, Miyamoto and Ashihara (2003) considered the measures to represent the degree of departure from marginal homogeneity (MH). Tomizawa (1984) considered an extended marginal homogeneity (EMH) model for square tables with ordered categories. This paper proposes a measure to represent the degree of departure from EMH. The measure proposed is expressed by using the Cressie and Read’s (1984) power-divergence or Patil and Taillie’s (1982) diversity index. The measure would be useful for comparing the degree of departure from EMH in several tables. Examples are given.

For square contingency tables with ordered categories, Agresti (1984, 2002) considered the marginal cumulative logistic (ML) model, which is an extension of the marginal homogeneity (MH) model. Miyamoto, Niibe and Tomizawa (2005) proposed the conditional marginal cumulative logistic (CML) model which is defined off the main diagonal cells, and gave the decompositions of the MH model using the ML (CML) model. This paper (1) considers the ML and CML models for multi-way tables, and (2) gives the decompositions of the MH model into the ML (CML) model and the model of the equality of marginal means for multi-way tables. An example is given.

For square contingency tables with ordered categories, this paper proposes some distance subsymmetry models. The one model indicates that the cumulative probability that an observation will fall in row category i or below and column category i + k (k ≥ 2) or above, is equal to the probability that it falls in column category i or below and row category i+k or above. This paper also gives the decomposition of the symmetry model into the marginal homogeneity model and some distance subsymmetry models. The father-son occupational mobility data in Britain and the women’s unaided vision data in Britain are analyzed.