How can I fit a function with many constants and coefficients?

Hello,

I am trying to do least-squares fitting of a messy function, which looks like this:

pixelResponseModel = p0_trans.*(Q0.*(1-percent_pol)./2 + ...
                     Q0.*(1-percent_pol)./2.*p0_contrast + ...
                     Q0.*percent_pol.*cos(p0_angle-anglesRadians).^2 + ...
                     Q0.*percent_pol.*sin(p0_angle-anglesRadians).^2.*p0_contrast);

Q0 and percent_pol are known constants that I would like to specify for each fit.

p0_trans, p0_contrast, and p0_angle are parameters which I want the fit to determine.

This is what I tried:

% Define the constants
Q0 = 50000;
percent_pol = 1;

% specify the dependent variable
anglesRadians = [0:180]*pi/180;

% specify the data to be fit
pixelResponseData = something; % this is a vector with data from the workspace

% I create the function using anonymous functions
modelFunction = @(p0_trans,p0_contrast,p0_angle,Q0,percent_pol,anglesRadians) p0_trans.*(Q0.*(1-percent_pol)./2 + Q0.*(1-percent_pol)./2.*p0_contrast + Q0.*percent_pol.*cos(p0_angle-anglesRadians).^2 + Q0.*percent_pol.*sin(p0_angle-anglesRadians).^2.*p0_contrast);

% I create the fit type
pixelResponseModel = fittype(modelFunction,'independent','anglesRadians','problem',{'Q0','percent_pol'},'coefficients',{'p0_trans','p0_contrast','p0_angle'});

% I run the fit
[fitobject] = fit(anglesRadians, medianPixel_11', pixelModel, 'problem', {'Q0', 'percent_pol'}, 'StartPoint', [50000, 1, 0.5, 0.1, 0] );

And I get the error:

Error using fit>iFit (line 367)
Too many inputs to FITTYPE function.

Error in fit (line 108)
[fitobj, goodness, output, convmsg] = iFit( xdatain, ydatain, fittypeobj, ...

Caused by:
    Failure in initial user-supplied objective function evaluation. LSQCURVEFIT cannot
    continue.

I don't think I'm using too many inputs...How else can I do this fit? I appreciate any help!