Interactive data analysis: a practical primer, by Donald R. McNeil. Pp xii, 186. £7. 1977. SBN 0 47102631 X (Wiley)

Missing-data-probleme in der

XI is of order n by PI and X 2 is of order n by P2. The partitioned correlation matrix is: standardized regression coefficients into unstandardized coefficients and by computing the intercepts. Before estimating missing data by Equation 1, the correlation matrix R must be estimated. Two methods can be used: Wilks (1932) proposes substituting the corresponding column mean for each missing entry; Glasser (1964) estimates R from all available pairs of scores for each pair of variables. The estimates obtained from Equation 1 can be improved by iteration. The estimates from one iteration can be used to improve the estimate of the correlation matrix for use in a next iteration. The program, however, becomes very expensive to run when the number of iterations is large. This procedure depends on the assumption that the data are missing at random and the estimates will be quite unsatisfactory when the missing variables do not correlate highly with at least one of the available variables and/or when the proportion of missing entries is large. Description. The main program uses a set of FORTRAN IV subroutines. These routines implement the estimation procedure and all supplementary operations. The subroutine WILKS computes the correlation matrix R by Wilks' (1932) method; GLASSER computes R by Glasser's (1964) method; TRANSF draws R 1 and RII from the relevant parts of R-I; REGRES estimates the missing entries according to Equation 1; CORR computes correlations and standard deviations; XMISS generates a data presence-absence matrix; GRINV is a matrix inversion routine that was published by Kaiser and Dickman (1972). The set also includes a matrix printing and punching routine. Input. The job deck consists of the following cards. Card 1 is the alphameric title; Card 2 specifies the number of rows (N) and columns (NP) of the data matrix; Card 3 contains the choice of procedure for computing R (NR) and the number of iterations (NRUN) , and it contains an option for punching the data matrix with estimated missing entries (NPU); Card 4 is the data format card (F-type variable format); Card 5 contains the code for missing entries. The next cards contain the raw data matrix. Each row of the data matrix must begin on a new card. The use of more than one card per row is permitted. Output. The printed output includes the titling information and, for each iteration, the correlation matrix, the data matrix with estimated missing entries, and corresponding means and standard deviations. The proportion of missing entries is also reported; the program gives a warning when this proportion exceeds the limit of .20. The data matrices with estimated missing entries can be punched as desired. Restrictions. The data matrix may not have more than 200 rows and 10 columns. These limits can easily (2) (1)

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A FORTRAN IV program for the estimation of missing data

/pdf/gcm-an-interactive-program-for-the-analysis-of-time-4iyaueieuk.pdf

GCM: An interactive program for the analysis of time-structured data

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Martijn P. F. Berger

Papers

A FORTRAN IV program for the estimation of missing data

GCM: An interactive program for the analysis of time-structured data

STP: A subroutine for simultaneous test procedures and confidence intervals