使用glmmTMB拟合beta_family模型后残差图出现模式的问题
比例数据建模:解决过/欠离散后残差存在模式的问题
问题背景
我正在处理比例数据,尝试多种模型解决过离散和欠离散问题:
- 初始使用二项分布模型时出现过离散
- 引入OLRE(过离散随机效应)后转为欠离散
- 改用
beta_family()拟合模型后,过离散与欠离散问题得到解决,但残差图显示存在明显模式
所有变量已完成标准化。
模型代码
bdd$prop <- (bdd$tot_paras) / bdd$puesta y <- cbind(bdd$tot_paras, bdd$nac) bdd$prop <- pmax(pmin(bdd$prop, 1 - 1e-5), 1e-5) y <- pmax(pmin(bdd$prop, 1 - 1e-5), 1e-5) mpt5 <- glmmTMB(y ~ altsca * coastsca * infestsca * NAO_t1sca + (1|site) + (altsca|year) + (1|id), family = beta_family(), data = bdd)
模型汇总结果
summary(mpt5) Family: beta ( logit ) Formula: y ~ altsca * coastsca * infestsca * NAO_t1sca + (1 | sitio) + (altsca | year) + (1 | id) Data: bdd AIC BIC logLik deviance df.resid -3046.9 -2910.8 1545.5 -3090.9 3581 Random effects: Conditional model: Groups Name Variance Std.Dev. Corr sitio (Intercept) 0.32707 0.5719 year (Intercept) 0.04375 0.2092 altsca 0.02278 0.1509 0.84 id (Intercept) 0.65928 0.8120 Number of obs: 3603, groups: sitio, 35; year, 12; id, 3603 Dispersion parameter for beta family (): 7.25 Conditional model: Estimate Std. Error z value Pr(>|z|) (Intercept) -0.85460 0.14358 -5.952 2.65e-09 *** altsca -0.59531 0.13203 -4.509 6.52e-06 *** coastsca -0.09911 0.12997 -0.763 0.445730 infestsca 0.15908 0.03603 4.415 1.01e-05 *** NAO_t1sca -0.08945 0.06985 -1.281 0.200322 altsca:coastsca -0.39947 0.17170 -2.327 0.019987 * altsca:infestsca 0.01210 0.04966 0.244 0.807511 coastsca:infestsca -0.10618 0.06121 -1.735 0.082811 . altsca:NAO_t1sca 0.08227 0.05643 1.458 0.144869 coastsca:NAO_t1sca -0.09151 0.03187 -2.871 0.004088 ** infestsca:NAO_t1sca 0.08243 0.02259 3.649 0.000263 *** altsca:coastsca:infestsca -0.11711 0.07914 -1.480 0.138915 altsca:coastsca:NAO_t1sca -0.08114 0.04026 -2.015 0.043858 * altsca:infestsca:NAO_t1sca -0.01356 0.02488 -0.545 0.585860 coastsca:infestsca:NAO_t1sca -0.02923 0.03031 -0.964 0.334825 altsca:coastsca:infestsca:NAO_t1sca -0.07461 0.03592 -2.077 0.037795 *
过离散检查结果
performance::check_overdispersion(mpt5) # Overdispersion test dispersion ratio = 0.887 p-value = 0.12
未检测到过离散。
残差与预测值情况
- 残差图:存在明显模式
- 观测值与预测值对比图:展示观测值和模型预测值的对应关系
内容的提问来源于stack exchange,提问作者KSN2
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