compare.relimp: Compare estimates of log odds, log odds ratios and relative...

In DECIDE: DEComposition of Indirect and Direct Effects

Compare estimates of log odds, log odds ratios and relative importance obtained by two datasets

Description

Computes 95% confidence intervals for the differences in log odds of transition, log odds ratios and relative importance estimates between the two datasets. Also calculates chi-squared test statistics and p-values for testing whether the differences are different from zero.

Usage

compare.relimp(dataset1, dataset2)

Arguments

dataset1	is the first dataset; a data frame with 4 columns, in the following order: 1: student's ID, 2: class, 3: transition (0 if not, 1 if yes) and 4: performance score.
dataset2	is the second dataset; a data frame with 4 columns, in the following order: 1: student's ID, 2: class, 3: transition (0 if not, 1 if yes) and 4: performance score.

Value

ci.diff.lo	95% confidence intervals for differences in log odds of transition
test.diff.lo	Test statistic for differences in log odds
test.diff.lo.pvalue	p-value for testing for differences in log odds
ci.diff.lor	95% confidence intervals for differences in log odds ratios
test.diff.lo	Test statistic for differences in log odds ratios
test.diff.lo.pvalue	p-value for testing for differences in log odds ratios
ci.diff.ri.1	95% confidence intervals for relative importance estimates - 1
ci.diff.ri.2	95% confidence intervals for relative importance estimates - 2
ci.diff.ri.avg	95% confidence intervals for relative importance estimates - average

Author(s)

Christiana Kartsonaki

References

Kartsonaki, C., Jackson, M. and Cox, D. R. (2013). Primary and secondary effects: Some methodological issues, in Jackson, M. (ed.) Determined to succeed?, Stanford: Stanford University Press.

Erikson, R., Goldthorpe, J. H., Jackson, M., Yaish, M. and Cox, D. R. (2005) On Class Differentials in Educational Attainment. Proceedings of the National Academy of Sciences, 102: 9730–9733

Jackson, M., Erikson, R., Goldthorpe, J. H. and Yaish, M. (2007) Primary and secondary effects in class differentials in educational attainment: The transition to A-level courses in England and Wales. Acta Sociologica, 50 (3): 211–229

Examples

# generate two datasets
set.seed(1)
data1 <- data.frame(seq(1:10), rep(c(1, 2), length.out = 10), 
c(rep(0, times = 3), rep(1, times = 7)), 
c(rnorm(4, 0, 1), rnorm(4, 0.5, 1), NA, NA))

data2 <- data.frame(seq(1:10), rep(c(1, 2), length.out = 10), 
c(rep(0, times = 5), rep(1, times = 5)), 
c(rnorm(5, 1, 1), rnorm(5, 0.5, 1)))

# run function
compare.relimp(data1, data2)

DECIDE documentation built on June 7, 2022, 1:08 a.m.