| BA.est {MethComp} | R Documentation |
A variance component model is fitted to method comparison data with replicate measurements in each method by item stratum. The purpose is to simplify the construction of a correct Bland-Altman-plot.
BA.est( data, linked=TRUE, exch=!linked )
data |
A data frame representing method comparison data with replicate
measurements, i.e. with variables meth, item,
repl and y. |
linked |
Are the replicated linked within item across methods? |
exch |
Are the replicated echangeable within (item,methods)? This is just for convenience. |
The model fitted is:
y=alpha_m + mu_i + c_mi + a_ir + e_ir, var(c_mi)=tau_m^2, var(a_ir)=nu^2, var(e_mir)=sigma_m^2
We can only fit separate variances for the tau's if more than
two methods are compared (i.e. nM > 2).
NOTE: Currently, the author is too ignorant about the ins and outs of lme
to find out how to get different tau's when nM>2.
Therefor the estimates in this case are equal i.e. from the model postulated.
A list with two elements:
bias |
Vector of estimates of alpha_m, the first element is always 0. |
variances |
Vector of variance components, nM tau's,
one nu if linked, and
nM sigma's. |
Bendix Carstensen
Carstensen, Simpson & Gurrin: Statistical models for assessing agreement in method comparison studies with replicate measurements, Preprent, Departmet of Biostatistics, University of Copenhagen, 2007, http://www.pubhealth.ku.dk/bs/publikationer/Research_report_07-14.pdf/.
data( ox ) BA.est( ox ) BA.est( ox, exch=TRUE ) data( sbp ) BA.est( sbp ) BA.est( sbp, exch=TRUE )