But ACMS drops out as a statistically significant predictor in a multiple regression when Y2H degree, a better estimator of non-specific protein-protein binding, is included.
Interestingly, the authors have shown that this patient underwent a rapid regression when treated with an EGFR inhibitor.
In men with penile lesions who harboured a similar HPV type as their female partner, we observed a delayed regression when couples did not use condoms compared to those who did.
The authors use a stepwise regression when other approaches such as logistic regressions, Ricker or Beverton Holt models could give more suitable results.
A graph including the three lines with the low growth plateaus is not modeled well using a linear regression (R = 3 × 10−4), while the data does fit a linear regression when these points are absent (R = 0.793).
Marshall et al.[ 26, 27] warned that using a multiple imputation that works well with less than 50% missing data introduces bias in a Cox regression when 75% of the data were missing.
The analytical approach employed by the authors doesn't seem appropriate in my view, as they also recognize in the discussion, and that could be the reason for not finding any climatic variable significant in the model: The authors use a stepwise regression when other approaches such as logistic regressions, Ricker or Beverton Holt models could give more suitable results.
Compared to the baseline treatment T B, the interaction rate is slightly higher in treatment T M. The difference is not significant when using one-sided Wilcoxon test with 8 independent observations (0.81 in T B vs 0.84 in T M, p > 0.10 ), but is significant in a Probit regression when controlling for heterogeneity of consumers (see Table 3).
Statistical tests for isolation-by-distance resulted in a significant regression when AHR1 diversity was compared among all sampled fishes (r = 0.530, p = 0.046), a relationship consistent with a neutral expectation, although distance explains only part of the difference in genetic diversity.
Conversely, MASK scores represent a count that is more appropriately analyzed using either a negative binomial regression when the variance is greater than the mean or a Poisson regression when the mean and variance are approximately equal [ 31].
