final deviance

USAGE SUMMARY

The phrase "final deviance" is correct and usable in written English.
It can be used in contexts discussing the last instance of deviation from a norm or standard, often in fields like sociology, psychology, or statistics. Example: "The study concluded with an analysis of the final deviance observed in the participants' behavior during the experiment."

✓ Grammatically correct

Science

Human-verified examples from authoritative sources

Exact Expressions

8 human-written examples

final deviance.

International Journal of STEM Education

In order to decide which model fits best, the final deviance can be taken into account.

Evolution: Education and Outreach

The final deviance indicates the likelihood of the observed data to fit the assumptions of the estimated model.

Evolution: Education and Outreach

The exclusion of this item led to a significant improvement in final deviance and favored the IRT model with 31 items (model with 32 items: final deviance dev = 18,085.76, np = 56; model with 31 items: dev = 17,344.36, np = 53; model comparison: Δ dev = 741.1, Δnp = 3, p < 0.001).

International Journal of STEM Education

These indexes are given as follows: AIC = dev + 2 n p BIC = dev + log N · n p, where 'dev' represents the final deviance of the model, N the sample size, and np the number of parameters for model estimation.

International Journal of STEM Education

Concerning the discriminant validity of the measures of the affective domain, the results in Table 3 indicate that in all dimensionalities, the PCM fits the data better than the RSM (cf. final deviance and information-based criteria).

Evolution: Education and Outreach

Human-verified similar examples from authoritative sources

Similar Expressions

52 human-written examples

In order to compare competing models, the information criteria and a χ2 likelihood ratio test of final deviances were used.

International Journal of STEM Education

A χ2 likelihood ratio test of final deviances (dev) was applied to test for significant differences between the models.

International Journal of STEM Education

Again, the faceted model with four correlated dimensions outperformed the single-factor approach, as the difference in the final deviances was statistically significant (Δ dev = 595.17, Δdf = 9, p < 0.001).

International Journal of STEM Education

The final model had a deviance of 122.806 at 1001 degrees of freedom and a p-value of 1.000 against the FM.

BMC Systems Biology

Table 3 shows that the predictive utility of the models, from the baseline to the final, improved in both deviance (from LR χ =39.1, p<0.05, to LR χ 2=11.5, p<0.05) and accuracy (from 69.6 to 73.2%).

Global Health Action

Expert writing Tips

Best practice

When discussing statistical models, clearly define what constitutes "deviance" in your specific context to avoid ambiguity. Specify the metric used to quantify it, such as residual deviance or model deviance.

Common error

Avoid using "final deviance" interchangeably with "variance." Deviance specifically refers to the difference between a fitted model and the saturated model, while variance measures the spread of data points around the mean. They are distinct concepts in statistical analysis.

Linguistic Context

The phrase "final deviance" functions as a noun phrase, typically used in statistical contexts to describe the deviance value of a model after all iterations or adjustments have been made. According to Ludwig AI, it indicates the likelihood of the observed data fitting the estimated model.

Expression frequency: Uncommon

Frequent in

Science

100%

Less common in

News & Media

0%

Formal & Business

0%

Academia

0%

Ludwig's WRAP-UP

The phrase "final deviance" is a technical term primarily used in statistical modeling to assess the goodness-of-fit of a model. As Ludwig AI confirms, it indicates the likelihood of the observed data to fit the assumptions of the estimated model. Its use is prevalent in scientific contexts, particularly in academic papers and research reports. While the phrase is grammatically correct, it's crucial to understand its specific meaning within statistical analysis to avoid misinterpretations. Alternatives exist, but their suitability depends on the precise context. The phrase highlights the importance of quantitative assessment in model selection and evaluation.

More alternative expressions

Phrases that express similar concepts, ordered by semantic similarity:

ultimate error

Focuses on the error aspect of deviance, indicating the last error observed.

end-stage deviation

Emphasizes the deviation aspect, suggesting the last stage of divergence.

terminal divergence

Highlights the divergence aspect, indicating the final point of separation.

conclusive anomaly

Focuses on the anomaly aspect, implying the last irregular point.

final variation

Highlights that it is the last amount of change or difference.

resultant discrepancy

Emphasizes the disagreement or difference resulting at the end.

eventual aberration

Focuses on the aberration, signaling the last deviation from what is normal or expected.

net deviation

Focuses on the overall deviation.

cumulative divergence

Highlights the accumulated divergence over a period, ending at a final point.

overall nonconformity

Emphasizes the total lack of conformity at the end.

FAQs

In statistical modeling, what does "final deviance" indicate?

The "final deviance" indicates the likelihood of the observed data to fit the assumptions of the estimated model. A smaller value generally suggests a better fit, as highlighted by Ludwig.

How can I use "final deviance" when comparing different statistical models?

The "final deviance" can be used, alongside information criteria like AIC and BIC, to compare how well different models fit the same data. Lower deviance, AIC, and BIC values often indicate a better model fit. A chi-square likelihood ratio test of final deviances can also test for significant differences between the models.

What's a good alternative to "final deviance" in scientific writing?

Depending on the specific context, alternatives like "ultimate error", "end-stage deviation", or "terminal divergence" can be used. These phrases emphasize different aspects of the concept.

How does "final deviance" relate to model selection?

"Final deviance" is a metric used in model selection to assess how well a statistical model fits the observed data. Models with lower final deviance are generally preferred, all other things being equal, as they indicate a better fit.