The null hypothesis is
against the alternative that at least one coefficient is nonzero. The code uses the scaled reduction in exponential-family deviance,
and compares it with .
That chi-squared calibration is appropriate when the dispersion is known, and is asymptotically valid after consistent dispersion estimation. With unknown Gamma dispersion, the standard finite-sample GLM comparison instead uses
against an distribution. Its p-value is approximately , so the correctly calibrated test still rejects at the 5% level and gives evidence that component type or position contributes to mean failure time.

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