Upper Graphic

This chart is generated by transforming the axes of the coordinate system according to a hypothetical relation between the variables. The functional form used here, is based on the assumption of exponentially increasing numbers of aids related deaths if tuberculosis prevalence is high. Although, both variables are mutually related, medical scientists would probably argue, that aids related deaths are influenced by tuberculosis prevalence rather than the other way around. So, just rotate the chart if that makes you feel more comfortable.

Lower Graphic

This plot shows a nonlinear regression line, which has been calculated by using the upper setting.

Program Code

Attention! For repeating the computation a transformed dataset is needed! If you have not yet computated and saved the transformation, run the program for transformation on the wikipage en:Analysis of Tuberculosis first!

library("xplore")
library("stats")

; ----- Reading Data ---------------------------------------------------------------------------

choose = "Read data from:"

defaults = "C:\Dokumente und Einstellungen\All Users\Desktop\UN_data_ordered.csv"

v1 = readvalue(choose, defaults)

x = readcsvm(v1)

data = x.double
country = x.text

; ----- Linear Regression of 0.8*log(Aids) on Tuberculosis ------------------------------------

ta = (0.8*log(data[,4]))~((data[,6]))

ta = paf(ta, isInf(ta[,1])==0)

nlreg = grlinreg(ta)

nlreg = setmask(nlreg, "line", "red")

; ----- Nonlinear Regression of Aids on Tuberculosis ------------------------------------------

{beta,bse,bstan,bpval} = linreg(ta[,1], ta[,2])

rx = #(0:max(data[,4]))

yq = beta[1] + beta[2]*log(rx)

rdata = sort (rx~yq)

rdata = setmask (rdata, "line", "red")

; ----- Results of Aids vs. Tuberculosis ------------------------------------------------------

setsize(800, 600)
d1 = createdisplay (2, 1)

; ----- Mark potentiell outliers --------------------------------------------------------------

text = country[data[24|43|70|65|9|33,1]]
tp = data[24|43|70|65|9|33,4|6]
tp2 = 0.8*log(data[24|43|70|65|9|33,4])~data[24|43|70|65|9|33,6]

setmaskt(tp, text, (1|2|3|4|5|6), (6|12|3|3|6|3))
setmaskt(tp2, text, (1|2|3|4|5|6), (6|12|3|3|6|3))
setmaskp(tp, (1|2|3|4|5|6))
setmaskp(tp2, (1|2|3|4|5|6))

; ----- Graphical Options ---------------------------------------------------------------------

show(d1, 1, 1, nlreg, ta, tp2)
show(d1, 2, 1, rdata, data[,4|6], tp)

title1 = "Linear Regression of Transformed Variables"
xaxis1 = "0.8 * log('Aids est. Death')"
yaxis1 = "Tuberculosis Prevelance per 100.000"
setgopt(d1, 1, 1, "title", title1, "ylabel", yaxis1, "xlabel", xaxis1)

title2 = "Equivalent Nonlinear Regression Line According to Hypothetical Relation"
xaxis2 = "Aids Estimated Death per 100.000"
yaxis2 = "Tuberculosis Prevelance per 100.000"
setgopt(d1, 2, 1, "title", title2, "ylabel", yaxis2, "xlabel", xaxis2)