Statistics: Matrix Calculation in Excel

A. Matrix Functions in Excel

  • MMULT(): returns the matrix product of 2 arrays. The result is an array with the same number of rows as array1 and the same number of columns as array2. Matrix A multiply Matrix B doesn’t equal to Matrix B multiply Matrix A. The order matters. The multiplication can be done as long as the number of columns of the first matrix equals to the number of rows in the second matrix. To make matrix smaller is to multiply a wider matrix to a long matrix, which returns the matrix with the shorter side of both matrices; and to make a matrix big is to multiple a longer matrix to a wider matrix, which returns the matrix with the longer side of both matrices.
  • MUNIT(): returns the identity matrix for the specified dimension.
  • MINVERSE(): returns the inverse matrix of a given matrix. The product of a matrix and its inverse matrix is the identity matrix. The inverse of a matrix will exist only if the determinant is not zero. The inverse of 2×2 [a, b; c, d] matrix can be calculated as:
    • Calculate the determinant;
    • take the inverse of the determinant;
    • multiple the inverse of the determinant to the [d, -b; -c, a] matrix.
  • MDETERM(): returns the determinant of the square matrix. If matrix determinant is 0, then matrix is sigular. For a 2×2 matrix, the determinant is equal to (ad-bc).

B. Excel Examples

  • Define matrix
Define X matrix
Define Y matrix
  • Transpose Matrix (X’)
Transpose X to X’ using array formula
  • Matrix multiplication
Multiplication of X’ and X
Multiplication of X’ and Y
  • Inverse Matrix (RULE: multiplication of a matrix and its inverse matrix equals to the identity matrix)
Inverse matrix of X’X
  • Combination of Matrices Operations
(X’X)^(-10)X’Y

C. Understand the matrix operation in solving regression equations

  • The matrix multiplication of X’X is to take the sum of product for each combination of all the Xs.
  • The inverse of X’X is converting the X’X into weights for Xs.
  • The matrix multiplication of X’Y is to take the sum of product for each combination of X and Y. Visually, it is like expand the space of X matrix to Y scale.
  • The (X’X)^(-1)X’Y is the estimation of the intercept and coefficient(s).

D. Reference

Data: Library Database Search Syntax for Systematic Review

A. Research Question:

A systematic review study is planned with the purpose of investigating whether current educational programs are effective for developing problem solving in early childhood education.

B. Terms and Definitions

  • Educational Programs
  • Problem Solving
  • Early Childhood

A. Reference for Systematic Review

A. Library Platforms and Databases

  • EBSCO
    • CINAHL
  • OVID
    • MedLine
    • EMBASE
    • PsychINFO
  • ProQuest
    • ERIC
    • PsychINFO

Same platform has same interface, nut the subject headings are different. Same database on different platforms has the same keywords for titles and abstracts, but different heading and different truncation and proximity syntactic rules.

Statistics: Calculate Effect Size for Meta-Analysis

A. Web-based Effect Size Calculator

B. Examples

  • T: Treatment Group
  • C: Control Group
  • T(n): n for Treatment Group
  • C(n): n for Control Group
  • p: p-value
  • std: standard deviation
DataES
1.
Mean SES / Group/ n / std
127.8 / T / 25 / 10.4
132.3 / C / 30 / 132.3
Standardized Mean Difference (d)
Means and Standard Deviation
d= -0.4466
2.
t/ T(n) / C(n)
1.68 / 10 / 12
Standardized Mean Difference (d)
T-Test, Unequal Sample Size
d= 0.7193
3.
T(n) / C(n) / p
10 / 12 / .037
Standardized Mean Difference (d)
T-Test P-Value, Unequal Sample Size
d= 0.9569
4.
r = .27 for binary variable and continuous variable
2*0.27/ sqrt(1-0.27^2)
ES=0.560829
formula from D.W. Wilson’s slides
5.
Group / Mean test scroe / n
1 / 55.38 / 13
2 / 59.40 / 18
3 / 75.14 / 37
4 / 88 / 22
F(3,86) = 7.05, for meta-analysis only interested group 1 and 2, std not reported.
Standardized Mean Difference (d)
F-Test, 3 or more Groups
d= -0.1658
6.
2 x 2 table
n / group / % not improved / % improved
42 / T / 32% / 68%
29 / C / 37% / 63%
Standardized Mean Difference (d)
Frequency Distribution (Proportions)
d= 0.1057

7. frequency table for T and C group, 60 cases for each group (no report of the means and stds)
Degrees of Condition / T(n) / C(n)
0 / 15 / 20
1 / 15 / 20
2 / 15 / 10
3 / 15 / 10
Standardized Mean Difference (d)
Frequency Distribution
d = 0.305
8. regression analysis with nonequivalent comparison group design
covariates: employment status, marital status, age etc.
treatment: intervention / probation only
unstandardized regression coefficient: -.523
std for DV, severity of physical abuse: s=9.23
sample size (intervention / probation only) : n1= 125 / n2=254
Standardized Mean Difference (d)
Unstandardized Regression coefficient
Covariates adjusted ES(d)= -0.0568
=(125-1)*9.23^2+ (254-1)*9.23^2 =32117.72
= 124+254-2 = 377
=32117.72 / 377 = 85.1929
=sqrt(85.1929)= 9.23 = S_pooled
ES=-.523 /9.23 = -.056

C. Web-based Calculator Output

Example 1: Means and Standard Deviation
Example 2: T-Test, Unequal Sample Size
Example 3: T-Test P-Value, Unequal Sample Size
Example 5: F-Test, 3 or more Groups
Example 6, Frequency distribution (Proportions)
Example 7, Frequency distribution
Example 8, Unstandardized Regression Coefficient

D. Citation

Wilson, D. B. (date of version). Meta-analysis macros for SAS, SPSS, and Stata. Retrieved November 3, 2019, from http://mason.gmu.edu/~dwilsonb/ma.html