function [cm, scaled] = CASTERMeasure(data)
%cm = CASTERMeasure(data)
%
% This function computes the CASTER measure of ICS response for a group of
% input asthma subjects.
%
% input DATA must be a matrix of sample data where:
%   column 1 = BURSTS (count)
%   column 2 = ED/Hospitalizations (count)
%   column 3 = PREFEV1 PP: pre-bronchodilator fev1 percent predicted 
%            (according to Hankinson equations for race/sex/age/height)
%   column 4 = LNPC20: natural log of PC20, methacholine challenge
%   column 5 = BDR %: percent change in FEV1 as a response to
%       bronchodilator (albuterol)
%
% output CM is the CASTER Measure of ICS Response, where higher is better.
% output SCALED is the CASTER measure scaled to be between 0 and 1 based on
%       the distribution of CASTER scores in the CAMP cohort.
%
%
%   (C) Michael McGeachie, 2019.  Open Source. 
%       Distributed under the MIT License.

% load weights / loadings and good/poor centroids:

loadings = [-0.000329	-0.01628	0.004081;...
            -0.000052	-0.003218	-0.000595;...
            0.002586	-0.000163	-0.000247;...
            0.000147	0.006293	0.027399;...
            -0.000011	-0.000545	-0.002436];
        
poorcent = [0.004058	-0.062759	0.032017];
goodcent = [0.012256	0.005799	0.027421];


% CENTERING:
data = data - mean(data);
pcs = data * loadings;


% compute CASTER measure (cm) here: 
dpoor = sum((pcs - poorcent).^2,2);
dgood = sum((pcs - goodcent).^2,2);

cm = dpoor - dgood;

minCAMP = -0.0188;
maxCAMP = 0.01;

scaled = (cm - minCAMP) / (maxCAMP-minCAMP);