fitting experimental data with the model + Monte-Carlo

Hello, I am trying to run this code and it's giving an error that matrix dimensions must not agree. I tried but did not resolve the issue. please suggest something

if 
function [fitresult, gof] = createFit(t, y)
t=[24.88503903 78.50497273 139.9636403 194.6529783 297.4975938 397.283713];
y=[45.00727678 36.79417319 37.5451424 33.05702304 30.41701789 28.98254504];
nsample=1000;
for i=1:nsample
  DD=1e12+2e12*randn(1);
  self_coff=0.08+0.04*randn(1);
  line_energy=0.5+0.5*randn(1);
  %conversion_factor=0.32+0.06*randn(1);
  threshold_stress=25.9e9*2.86e-10.*sqrt(DD).*((0.5.*line_energy)+sqrt(self_coff));
  ave_strainrate=2.86e-10*1e12.*sqrt(DD);
[xData, yData] = prepareCurveData( t, y );
ft = fittype( strcat('(',num2str(threshold_stress)),'+((0.89.*s)*(1-((8.617e-5.*x)./F).*log(6.667e-4,'./strcat('(',num2str(ave_strainrate)),'))).^(1/q))^(1/p)))./(0.33))', 'independent', 'x', 'dependent', 'y');.
opts = fitoptions( 'Method', 'NonlinearLeastSquares' );
opts.Display = 'Off';
opts.Lower = [1.1 0.667 1.5 3];
opts.StartPoint = [1.8 0.667 1.5 4];
opts.TolX = 1;
opts.Upper = [3.2 0.667 1.5 25];
end 
% Fit model to data.
[fitresult, gof] = fit( xData, yData, ft, opts );
end