where for the reference standard and the test sample respectively:
is the response at dose , is the intercept and is the slope.
is an error term with distribution so is the error with distribution .
Analysis options
The linear model offers all the common analysis options and the following specific one.
Selecting the linear part of the dose response curve
If the data are expected to exhibit some curvature, perhaps for very high or low potency test samples, it may be required to exclude dose groups at one end of the dose range in order to achieve a linear dose-response. QuBAS allows for the sequential exclusion of dose groups, starting either at the top end or at the bottom end, whereby dose groups are excluded in turn until the test for linearity is passed.
The user selects:
• Low dose end
• High dose end
• Both dose ends
• P value for linearity (default p = 0.05)
System Suitability Criteria
The linear model has the standard sample suitability criteria, see here.
Reference standard
Goodness of fit of the model, or ‘linearity’
A quadratic model can be fitted to the data and the significance of the quadratic term tested via a t test.
The level (critical p value) can be chosen by the user.
• Default is 0.01.
b) The for the regression can be calculated.
The minimum value must be chosen by the user (no default setting).
Parameter values
a) Ranges for parameter values can be set.
b) Equivalence limits for can be set:
Ranges for the confidence intervals for (no default setting).
The confidence level for the each interval can be chosen by the user (no default setting).
Statistical significance of the slope
,
a) , via a one-sample t test comparing the slope with zero.
• The level (critical P value) can be chosen by the user
Default is 0.05.
• The sign of the slope must be stated (positive or negative).
Sample Suitability Criteria
The linear model offers all the common sample suitability criteria.
Result (estimated concentration)
The concentration of the sample is estimated with a parallel model built with the parameters of the standard curve.
is the response at 
dose 
, 
is the intercept and 
is the slope.
is an error term with distribution 
so 
is the error with distribution 
.
for the regression can be calculated.
can be set.
, via a one-sample t test comparing the slope with zero.