The phrase "analysis of deviance showed" is correct and usable in written English.
It can be used in academic or research contexts when discussing findings related to deviance in a sociological or psychological study.
Example: "The analysis of deviance showed a significant correlation between social factors and criminal behavior."
Alternatives: "study of deviance revealed" or "examination of deviance indicated".
Full details are given in Tables 2 and 3. > -wrap-foot> > -wrap-foot> For cases diagnosed during 1987–2003, analysis of deviance and the Akaike Information Criterion showed that, after allowing for sex and age, population density was not significant (P = 0.157).
We then used an analysis-of-deviance approach to test whether a nonlinear function improved the model fit compared with a linear term.
All models were fitted to datasets that excluded missing education values to enable analysis of deviance; the sample sizes are shown in the "Complete N" columns in Appendix A. Inclusion of a sibling coefficient in Model 2 substantially improves the fit, as does inclusion of education (and the religious commitment variable from the ISSP data) in Model 3.
Table 4 shows the results of analysis of deviance for model comparison.
Analysis of deviance to examine the association of GP88 with each clinical indicator showed that GP88 was independent of patients' demographics, such as age and ethnicity, of tumor characteristics, such as tumor size, tumor grade, PR status, disease stage and lymph node status, and of treatments.
Analysis for model comparison showed that the combined-PI predictor added significant information to tumor size and TP53 mutations (analysis of deviance p = 0.04; Akaike's Information Criterion AICC) for model with and without combined-PI = 191.8 and 194.01, respectively; Table S2).
We experimentally observed differences in susceptibility to both carbaryl and potassium dichromate among the studied pond populations of D. magna (analysis of deviance, P < 0.001).
Model selection was carried out using Akaike's Information Criterion (AIC) [29] and analysis of deviance.
The binary mildew infection data were analysed using multiple logistic regression with analysis of deviance [30].
In the shallowest depth zone (50 150 m), a linear model was sufficient (analysis of deviance, p = 0.12) to describe the relation between AvTD and latitude.
