불균형 자료 분석과 가설 검정에 관한 연구 = Study on the analysis of disproportionate data and hypothesis testing

국문 초록 (Abstract)

불균형 자료 분석에 대해서는 일찍이 Brown(1932)과 Yates(1934)의 연구 이에 Finney(1948), Stevens(1948), Henderson(1953), Kramer(1955)등 많은 사람들이 관심을 가지고 연구하였고 Searle(1971, 1977, 1981)은 R(v) 표기법으로 모형식의 상수적합에 의한 변동을 나타내었으며 Hocking과 Speed(1975), Speed와 Hocking (1976)이 사용한 제한들을 $\Sigma$ -, W-, O-restrictions라고 하였다. 또한 Speed등(1978)은 비가중평균법(method of unweighted means), 평균의 가중제곱법(method of weighted squares of means), 상수적합법 (method of fitting constants), Overall- Spiegel법, Henderson방법 등을 비교설명하고 Burdick 등(1974)은 각 변동을 기하학적으로 해석하려 하였다. 백(1987a,1987b)은 SAS 팩키지에 의한 변동을 설명하였고 장(1988)도 Searle(1977, 1981)의 방법을 이용하여 가설검정과 변동을 검토한바 있다. 본 연구에서는 여러 가지 모형에 대하여 $n_{ij} > 0, 또는 n_{ij} \geq 0$ 인 경우에 변동계산과 W-, $\Sigma$-, O- 제한 조건하에서의 변동과 가설을 재조명해 보고져 한다.

다국어 초록 (Multilingual Abstract)

In the present study two sets of unbalanced two-way cross-classification data with and without empty cell(s) were used to evaluate empirically the various sums of squares in the analysis of variance table. Searle(1977) and Searle et.al.(1981) developed a method of computing R($\alpha$\mid$\mu, \beta$) and R($\beta$\mid$\mu, \alpha$) by the use of partitioned matrix of X'X for the model of no interaction, interchanging the columns of X in order of $\alpha, \mu, \beta$ and accordingly the elements in b. An alternative way of computing R($\alpha$\mid$\mu, \beta$), R($\beta$\mid$\mu, \alpha$) and R($\gamma$\mid$\mu, \alpha, \beta$) without interchanging the columns of X has been found by means of,$(X'X)^-$ derived, using $W_2 = Z_2Z_2-Z_2Z_1(Z_1Z_1)^-Z_1Z_2$. It is true that $R(\alpha$\mid$\mu,\beta,\gamma)\Sigma = SSA_W and R(\beta$\mid$\mu,\alpha,\gamma)\Sigma = SSB_W$ where $SSA_W$ and means analysis and $R(\gamma$\mid$\mu,\alpha,\beta) = R(\gamma$\mid$\mu,\alpha,\beta)\Sigma$ for the data without empty cell, but not for the data with empty cell(s). It is also noticed that for the datd with empty cells under W - restrictions $R(\alpha$\mid$\mu,\beta,\gamma)_W = R(\mu,\alpha,\beta,\gamma)_W - R(\mu,\alpha,\beta,\gamma)_W = R(\alpha$\mid$\mu) and R(\beta$\mid$\mu,\alpha,\gamma)_W = R(\mu,\alpha,\beta,\gamma)_W - R(\mu,\alpha,\beta,\gamma)_W = R(\beta$\mid$\mu) but R(\gamma$\mid$\mu,\alpha,\beta)_W = R(\mu,\alpha,\beta,\gamma)_W - R(\mu,\alpha,\beta,\gamma)_W \neq R(\gamma$\mid$\mu,\alpha,\beta)$. The hypotheses $H_o : K' b = 0$ commonly tested were examined in the relation with the corresponding sums of squares for $R(\alpha$\mid$\mu), R(\beta$\mid$\mu), R(\alpha$\mid$\mu,\beta), R(\beta$\mid$\mu,\alpha), R(\alpha$\mid$\mu,\beta,\gamma), R(\beta$\mid$\mu,\alpha,\gamma), and R(\gamma$\mid$\mu,\alpha,\beta)$ under the restrictions.