Sentence examples for data deviance from inspiring English sources

The model that assumed that the probability of honeybees visiting spider inflorescences was independent of spider attributes, but not necessarily equal to 1/3, provided only a slightly better fit to the data (deviance  = 2.92, df = 1, P = 0.08).

Although the deviance of the final model suggested that main effects fit very well the data (deviance = 1,481 with DF = 2,106; p = 1.00), we looked for additional two-way interaction effects using a backward selection.

There was no evidence of lack of fit by studying deviance on collapsed data (deviance =259 on 279 ddl, P = 0.23) or by graphical procedure.

2LB: Two layer bandage; 4LB: Four layer bandage; AIC: Akaike information criteria; AD: Aggregate data; DIC: Deviance information criteria; HH: Two layer hosiery; HTA Healthh technology assessment; IPD: Individual patient-level data; MCMC: Markov chain Monte Carlo; NMA: Network meta-analysis; RCT: Randomised controlled trial; SSB: Short stretch bandage; ZINC: Zinc paste bandage.

14 Inconsistency was additionally evaluated by inspection of the goodness of fit of the model to the data with residual deviance; the model was considered to provide an adequate fit when the mean of the residual deviance was similar to the number of data points of the model.

We concluded that the model (Precip + UH + CH) received considerable support by data with the deviance weight of 0.43.

Under the null hypothesis that the model provides an adequate fit to the data, the residual deviance is expected to have a mean equal to the number of unconstrained data points.

Deviance is a measure of deviation between the model and the data: the greater the deviance, the greater the deviation from the model.

Regarding the severity of abuse or dependence (our cannabis patients used this drug on average on 62% of the days of a month; Deas et al. [ 28] reported only half as many drugs for their cannabis users) and social deviances (data from the subgroup: 41.5% present comorbid conduct disorder), our sample represents a highly affected and deviant group of drug using adolescents.

Deviance is a measure of how well the statistical model describes the observed data, with a lower deviance implying a better fit (see Appendix for details).

The decision-tree algorithm divides the data to reduce the deviance, and classifies them into the pre-defined categories as many tree branches.