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...int which the curve has reached half the plateau), and more... The recovery of fluorescence in the ROI is used as a measurement of protein diffusion in the time range of the experiment. A steep curve means that the molecules has diffused rapidly into the observed ROI and vice versa. When I do a regressional curve fit without any constraints I get a huge deviation from the measured value and the fitted curve at the first data point in the curve (se the bottom picture). My question is simply: can I constrain the fitting so that the first point used in fitting is equal to the measured first point? Also,...

...using the outcome of the regression, but I just certain patients involved in the prediction. So, I want to use the estimated parameters of the full regression, but after that, I only want patients with certain characteristics in my prediction matrix. For example, only patients with BMI >25. My regressional formula looks as follows: fit = glmer(response ~ sex+bmi+asa+ (1|center), data=data, family=binomial), and my normal prediction formula: pred=fit@X %*% fit@fixef. I hope someone can help me! Greetings, Alex [[alternative HTML version deleted]]

Hello together, this is ma first post, so please aplogize me if post this in the wrong section. I have problem concerning ma two matrizes. After a regressione and so on, I got two matrizes Matrixres contains the results of ma calculation. Matrixr contains my detiene, which where Aldo used for the regression. Please ser the following code: #Datei einlesen residual =