R语言用stargazer输出三个面板固定效应模型遇报错，求解决

我用plm包的within模型拟合了三个含id和年份双重固定效应的面板线性模型：

fixed_YIELD_mean_to_treat.100 <- plm(YIELD_mean_total ~  treated.100 + Nightlight_sum + Population_sum + temp_mean, data= Results, index = c("id", "year"), model = "within")
fixed_YIELD_mean_fruits_treat.100<- plm(YIELD_mean_Fruit ~  treated.100 + Nightlight_sum + Population_sum + temp_mean, data= Results, index = c("id", "year"), model = "within")
fixed_YIELD_mean_grain_treat.100<- plm(YIELD_mean_Cereal ~  treated.100 + Nightlight_sum + Population_sum + temp_mean, data= Results, index = c("id", "year"), model = "within")

随后尝试用stargazer将三个模型合并输出到HTML文件：

stargazer( fixed_YIELD_mean_to_treat.100, fixed_YIELD_mean_fruits_treat.100, fixed_YIELD_mean_grain_treat.100, 
           type = "html",
           align = TRUE,
           omit = c("year", "id"),
           omit.labels = c("year FE", "id FE"),
           add.lines= list(c("ID Fixed effects", "Yes", "Yes", "Yes"),
                          c("Time Fixed effects", "Yes", "Yes", "Yes")),
           out = ".test1.html" )

但触发错误：

Error in if (is.na(s)) { : the condition has length > 1

仅输出两个模型时可正常运行，求三个模型合并输出的解决办法。

• 检查模型对象一致性：确认三个plm模型的结构完全匹配，比如index参数、数据集来源、变量结构无差异。可以用str()查看每个模型的内部结构，对比coefficients、model等核心部分是否一致，避免某模型因数据异常导致结构偏差。
• 调整stargazer参数：原代码中omit = c("year", "id")可能在多模型场景下引发识别冲突，尝试替换为omit = "fixed"（plm的within模型固定效应会被标记为fixed），或直接移除omit与omit.labels参数，改用keep.stat = c("n", "adj.rsq")保留所需统计量，绕过固定效应的识别问题。
• 更新依赖包：旧版本的plm或stargazer可能存在多模型输出的兼容性bug，运行update.packages(c("plm", "stargazer"))更新至最新版本后重试。
• 替换输出工具：如果上述方法无效，改用texreg包替代stargazer，它对plm模型的多模型支持更稳定：

  library(texreg)
  htmlreg(list(fixed_YIELD_mean_to_treat.100, fixed_YIELD_mean_fruits_treat.100, fixed_YIELD_mean_grain_treat.100),
          file = ".test1.html",
          add.lines = list(c("ID Fixed effects", "Yes", "Yes", "Yes"),
                          c("Time Fixed effects", "Yes", "Yes", "Yes")))
  

内容的提问来源于stack exchange，提问作者Sulz