COVID-19 High Frequency Phone Survey of Households 2020, Round 2 - Viet Nam

Geographic coverage
---------------------------

National, regional

Analysis unit
---------------------------

Households

Kind of data
---------------------------

Sample survey data [ssd]

Sampling procedure
---------------------------

The 2020 Vietnam COVID-19 High Frequency Phone Survey of Households (VHFPS) uses a nationally representative household survey from 2018 as the sampling frame. The 2018 baseline survey includes 46,980 households from 3132 communes (about 25% of total communes in Vietnam). In each commune, one EA is randomly selected and then 15 households are randomly selected in each EA for interview. We use the large module of to select the households for official interview of the VHFPS survey and the small module households as reserve for replacement. After data processing, the final sample size for Round 2 is 3,935 households.

Mode of data collection
---------------------------

Computer Assisted Telephone Interview [cati]

Research instrument
---------------------------

The questionnaire for Round 2 consisted of the following sections

Section 2. Behavior
Section 3. Health
Section 5. Employment (main respondent)
Section 6. Coping
Section 7. Safety Nets
Section 8. FIES

Cleaning operations
---------------------------

Data cleaning began during the data collection process. Inputs for the cleaning process include available interviewers’ note following each question item, interviewers’ note at the end of the tablet form as well as supervisors’ note during monitoring. The data cleaning process was conducted in following steps:
• Append households interviewed in ethnic minority languages with the main dataset interviewed in Vietnamese.
• Remove unnecessary variables which were automatically calculated by SurveyCTO
• Remove household duplicates in the dataset where the same form is submitted more than once.
• Remove observations of households which were not supposed to be interviewed following the identified replacement procedure.
• Format variables as their object type (string, integer, decimal, etc.)
• Read through interviewers’ note and make adjustment accordingly. During interviews, whenever interviewers find it difficult to choose a correct code, they are recommended to choose the most appropriate one and write down respondents’ answer in detail so that the survey management team will justify and make a decision which code is best suitable for such answer.
• Correct data based on supervisors’ note where enumerators entered wrong code.
• Recode answer option “Other, please specify”. This option is usually followed by a blank line allowing enumerators to type or write texts to specify the answer. The data cleaning team checked thoroughly this type of answers to decide whether each answer needed recoding into one of the available categories or just keep the answer originally recorded. In some cases, that answer could be assigned a completely new code if it appeared many times in the survey dataset.
• Examine data accuracy of outlier values, defined as values that lie outside both 5th and 95th percentiles, by listening to interview recordings.
• Final check on matching main dataset with different sections, where information is asked on individual level, are kept in separate data files and in long form.
• Label variables using the full question text.
• Label variable values where necessary.

地理覆盖范围
---------------------------
全国、区域
分析单元
---------------------------
家庭
数据类型
---------------------------
样本调查数据 [ssd]
抽样程序
---------------------------
2020年越南COVID-19高频电话调查（VHFPS）采用2018年全国代表性家庭调查作为抽样框架。2018年的基线调查包括来自3132个社区（约占越南总社区的25%）的46,980个家庭。在每个社区中，随机选择一个EA，然后在每个EA中随机选择15个家庭进行访谈。我们使用大型模块从VHFPS调查的官方访谈中选择家庭，并将小型模块家庭作为备选。数据处理后，第2轮的最终样本量为3,935个家庭。
数据收集方式
---------------------------
计算机辅助电话访谈 [cati]
研究工具
---------------------------
第2轮的调查问卷包括以下部分
第2节：行为
第3节：健康
第5节：就业（主要受访者）
第6节：应对策略
第7节：安全网
第8节：FIES
数据清洗操作
---------------------------
数据清洗始于数据收集过程中。清洗过程的输入包括每个问题项后的可用访谈员笔记、平板表尾的访谈员笔记以及监控过程中的监督员笔记。数据清洗过程按以下步骤进行：
• 将使用少数民族语言访谈的家庭与主要使用越南语访谈的基层数据集合并。
• 删除由SurveyCTO自动计算的冗余变量。
• 删除数据集中提交超过一次的相同表格的家庭重复项。
• 删除根据确定的替换程序不应接受访谈的家庭的观测值。
• 格式化变量为它们的对象类型（字符串、整数、小数等）。
• 检查访谈员笔记并根据需要进行调整。在访谈过程中，当访谈员难以选择正确的代码时，建议选择最合适的代码，并详细记录受访者的答案，以便调查管理团队进行合理化判断并做出最佳代码选择的决定。
• 根据监督员的笔记更正错误输入的代码。
• 重新编码答案选项“其他，请指定”。此选项通常后跟一个空白行，允许访谈员输入或书写以指定答案。数据清洗团队将彻底检查此类答案，以决定每个答案是否需要重新编码到可用的类别之一，或者仅保留原始记录的答案。在某些情况下，如果该答案在调查数据集中出现多次，则可以分配一个全新的代码。
• 通过听取访谈录音来检查异常值的数据准确性，异常值定义为位于第5和第95百分位之外的价值。
• 对匹配主数据集与不同部分进行最终检查，其中询问的信息在个人层面上保持单独的数据文件和长格式。
• 使用完整的问题文本标记变量。
• 在必要时标记变量值。