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Volume II incorporates all the situations presented in Volume I, except for Section V, and adds the condition of missing observations of the covariate and/or response variables. Volume II presents the theoretical development of the analysis of multivariate covariance in which missing values occur among both dependent and independent variables and presents an example.

This report reviews the theoretical framework which permits analysis of multivariate covariance data in which missing values occur among both dependent and independent variables. A flow chart and program listing is given for a computer program which will estimate the block and treatment parameters, as well as the regression coefficients for the covariates. The program will also calculate test statistics for testing hypotheses which are supplied by the user. It should be pointed out that this program allows for only two categories of design indicator variables, namely a block effect and a treatment effect which are assumed to be additive. The program is thus suitable for the usual randomized block model with additive block and treatment effects, or a general two-factor additive effects model (i.e., no interaction), or the usual one-way classification model (i.e., several treatments but only one block). It will not accommodate more complex designs such as a Latin Square Layout with a multivariate response and one or more covariates. User instructions and a worked example are provided in this volume. (Author)

The present analysis deals with very high-dimensional data sets, each one containing close to nine hundred binary variables. Each data set corresponds to an evaluation of one complex system. These data sets are characterized by large portions of missing data where, moreover, the unobserved variables are not the same in different evaluations. Thus, the problems which confront the statistical analysis are those of multivariate binary data analysis, where the number of variables is much larger than the sample size and in which missing data varies with the sample elements. The variables, however, are hierarchically structured and the problem of clustering variables to groups does not exist in the present study. In order to motivate the statistical problem under consideration, the Marine Corps Combat Readiness Evaluation System (MCCRES) is described for infantry battalions and then used for exposition. The present paper provides a statistical model for data from MCCRES and develops estimation and prediction procedures which utilize the dependence structure. The E-M algorithm is applied to obtain maximum likelihood estimates of the parameters of interest. Numerical examples illustrate the proposed methods.

The present analysis deals with very high-dimensional data sets, each one containing close to nine hundred binary variables. Each data set corresponds to an evaluation of one complex system. These data sets are characterized by large portions of missing data where, moreover, the unobserved variables are not the same in different evaluations. Thus, the problems which confront the statistical analysis are those of multivariate binary data analysis, where the number of variables is much larger than the sample size and in which missing data varies with the sample elements. The variables, however, are hierarchically structured and the problem of clustering variables to groups does not exist in the present study. In order to motivate the statistical problem under consideration, the Marine Corps Combat Readiness Evaluation System (MCCRES) is described for infantry battalions and then used for exposition. The present paper provides a statistical model for data from MCCRES and develops estimation and prediction procedures which utilize the dependence structure. The E-M algorithm is applied to obtain maximum likelihood estimates of the parameters of interest. Numerical examples illustrate the proposed methods.

1Little Sister Snow

By Frances Little

American author Fannie Caldwell, under pen name of Frances Little, tells the story of young Yuki San growing up in Japan circa early 1900s, and of her dreams of an American. (Introduction by Cheri Gardner)

2Little Sister Snow (version 2)

By Frances Little

This is a story of a little Japanese girl, her life in Japan and her loves. The story opens just before the festival of Hinamatsuri on the third day of the third month, which was set apart as the big birthday of all little girls born in the lovely island, and was celebrated by the Festival of Dolls, which is celebrated on March 3rd throughout Japan for the well being of young girls, praying for their prosperous health. Isn’t it touching? Here is this country (Japan) who graciously honors a girl child through an ancient festival for their safety expunging the bad spirits from the dolls. <br> Yuki San is the young daughter of an old Japanese couple. She's spoiled, sassy, and (in my opinion) quite naughty. The couple tried for many, many years to have a baby and finally Yuki was born. In their eyes she can do no wrong. She is their blessing and will care for them in their final years of life. One day Yuki decides to drown her kitten by throwing it into a gutter that leads to the ocean. Her plan is interrupted by an American teen, Richard Merrit but that's all I'm going to say. You will need to listen to this wonderful tale to find out the surprising stuff that happens to them both. Oh, there is a pre-arranged marriage involved here. (Summary by Phil Chenevert)

Maybe--tomorrow, by Jay Little (pseudonym for Clarence Lewis Miller) published in 1952* based in the confusing latter part of his teenage years, tells the story of the introverted and forlorn Gaylord LeClarie coming to terms with the world around him and who he is. Gaylord must navigate everything from sex, his own sexuality and his own gender identity. friendship, Love and self-acceptance in a sometimes hostile world... - Summary by Curt Troutwine