Not exact matches
Individual growth
curve models were developed for multilevel analysis and specifically designed for exploring longitudinal data on individual changes over time.23 Using this approach, we applied the MIXED procedure in SAS (SAS Institute) to account for the random effects of repeated measurements.24 To specify the correct model for our individual growth
curves, we compared a series of MIXED models by evaluating the difference in deviance between nested models.23 Both fixed quadratic and cubic MIXED models
fit our data well, but we selected the fixed quadratic MIXED model because the addition of a cubic time term was not statistically
significant based on a log - likelihood ratio test.
He used the Lomb - Scargle routine in IDL to determine the most
significant periodicity in the data (= 3.2 days), and then used this as input into a least - squares sine wave
fit to produce the
fitted curve shown.
With respect to
curve fitting, I get an R ^ 2 of 0.8785 regressing these data on a 250 year cycle with statistically
significant harmonics at 125 years and 62.5 years.
We thus find that there is no
significant correlation of the CRF
curve from Shaviv's model and the temperature
curve of Veizer, even after one of the four CRF peaks was arbitrarily shifted by 40 m.y. to improve the
fit to the temperature
curve.