snha (version 0.1.3)

snha-package: snha package - association chain graphs from correlation networks

Description

The snha package can be used to construct association chain graphs based on the St. Nicolas House Analysis (SNHA) algorithm as described in Groth et. al. 2019. and Hermanussen et. al. 2021.

Value

No return value

Author

Detlef Groth <[e-mail]>

Details

The package provides the following functions: Function for graph generation from data:

snha(data)

applys the SNHA method on the data and returns a new snha graph object

S3 methods for snha graphs:

plot.snha(x)

plots a snha graph

as.list.snha(x)

return a list representation of a snha graph object

Utility functions:

snha_get_chains(g)

returns the chains found by the algorithm as matrix

snha_graph2data(A)

create for the given adjacency matrix some data with the appropiate correlations

snha_layout(g)

calculate layout coordinates for the given graph or adjacency matrix

snha_ll(g,chain)

calculate log-likelihood for the given chain of the snha graph

snha_rsquare(data,g)

for given data and graph or adjacency matrix calculate linear model r-square value

References

• Groth, D., Scheffler, C., & Hermanussen, M. (2019). Body height in stunted Indonesian children depends directly on parental education and not via a nutrition mediated pathway - Evidence from tracing association chains by St. Nicolas House Analysis. Anthropologischer Anzeiger, 76 No. 5 (2019), p. 445 - 451. tools:::Rd_expr_doi("10.1127/anthranz/2019/1027")

• Hermanussen, M., Assmann, & Groth, D. (2021). Chain Reversion for Detecting Associations in Interacting Variables - St. Nicolas House Analysis. International Journal of Environmental Research and Public Health. 18, 4 (2021). tools:::Rd_expr_doi("10.3390/ijerph18041741").

• Novine, M., Mattsson, C. C., & Groth, D. (2021). Network reconstruction based on synthetic data generated by a Monte Carlo approach. Human Biology and Public Health, 3:26. tools:::Rd_expr_doi("10.52905/hbph2021.3.26")

Examples

library(MASS) 
data(birthwt) 
as=snha(birthwt[,-1]) 
plot(as) 
as$theta 
ls(as) 
data(decathlon88) 
head(decathlon88) 
dec=snha(decathlon88,method="spearman",alpha=0.1) 
plot(dec,layout='sam')