However, the appropriateness of treating interactions between the year and other categorical variables as random effects is arguable in many situations, such as when the interaction cannot be completely explained as a random effect (e.g., it shows a significant trend) [ 63 ].
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Data reconstruction can improve abundance index estimation: An example using Taiwanese longline data for Pacific bluefin tuna.
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The ANOVA indicated a highly significant relationship and significance effects of all explanatory variables.