Accurate and precise estimates of under-5 mortality rates (U5MR) are an important health summary for countries. Full survival curves are additionally of interest to better understand the pattern of mortality in children under 5. Modern demographic methods for estimating a full mortality schedule for children have been developed for countries with good vital registration and reliable census data, but perform poorly in many low- and middle-income countries. In these countries, the need to utilize nationally representative surveys to estimate U5MR requires additional statistical care to mitigate potential biases in survey data, acknowledge the survey design, and handle aspects of survival data (i.e., censoring and truncation). In this paper, we develop parametric and non-parametric pseudo-likelihood approaches to estimating under-5 mortality across time from complex survey data. We argue that the parametric approach is particularly useful in scenarios where data are sparse and estimation may require stronger assumptions. The nonparametric approach provides an aid to model validation. We compare a variety of parametric models to three existing methods for obtaining a full survival curve for children under the age of 5, and argue that a parametric pseudo-likelihood approach is advantageous in low- and middle-income countries. We apply our proposed approaches to survey data from Burkina Faso, Malawi, Senegal, and Namibia. All code for fitting the models described in this paper is available in the R package pssst.

翻译：[translated abstract in Chinese] 精确且准确的5岁以下儿童死亡率（U5MR）估计是各国重要的健康总结指标。为更好地理解5岁以下儿童的死亡模式，完整的生存曲线也备受关注。针对拥有完善生命登记系统和可靠普查数据的国家，现代人口统计学方法已开发出完整的儿童死亡时间表估计方案，但在许多中低收入国家中表现欠佳。在这些国家，利用具有全国代表性的调查数据来估计U5MR需要更严谨的统计处理，以减轻调查数据中潜在偏差、考虑调查设计特征并处理生存数据的特殊性问题（即删失与截断）。本文针对复杂调查数据，提出了参数与非参数伪似然方法，用于跨时间段的5岁以下儿童死亡估计。我们认为参数法在数据稀疏且需更强假设的情景下尤为有效，而非参数法则为模型验证提供辅助工具。我们将多种参数模型与三种现有方法进行对比——这些方法均用于获取5岁以下儿童的完整生存曲线，并论证了参数伪似然法在中低收入国家中的优势。我们将提出的方法应用于布基纳法索、马拉维、塞内加尔和纳米比亚的调查数据。本文所述模型的所有拟合代码均收录于R包"pssst"中。