Preparing Time Diary Data to Create Tempograms and to Conduct Sequence Analysis

By Sarah Flood and Kamila Kolpashnikova

Time diary data: a unique opportunity

Time diary data offer researchers an opportunity to visualize daily life in a way that just isn’t possible with other data and demonstrating how people spend time. Respondents report every activity that they engage in (along with where and who they were with) over the course of the day, which means that time diaries can indicate how much time was spent in various activities as well as when activities occur during the day (e.g., timing) and the order in which they occur (i.e., sequencing) . This blog post will describe how to transform IPUMS ATUS data to perform these types of analyses, illustrate how to create a tempogram (including sample code), and link to additional resources for creating tempograms and performing sequence analysis.

While there are several ways to leverage the unique properties of time diary data, analysts are increasingly interested in creating tempograms and conducting sequence analyses, both of which capitalize on the temporal specificity of time diary data. These techniques allow researchers to explore the timing and order of activities over the course of a day. Both creating tempograms and conducting sequence analysis require time units that are consistent across respondents. Most time diary data are not natively in this format.

Continue reading…

IPUMS FAQ: Alternative Measures of Unemployment

By Matthew Bombyk

As part of the IPUMS mission to democratize data, our User Support team strives to answer your questions about the data. Over time, some questions are repeated. This blog post is an extension of an earlier series addressing frequently asked questions. Maybe you’ll learn something. Perhaps you’ll just find the information interesting. Regardless, we hope you enjoy it!

Here’s one of those questions:

How can I use IPUMS CPS to calculate the Alternative Measures of Unemployment published by the BLS?

Every month the Bureau of Labor Statistics (BLS) publishes a set of Alternative Measures of Labor Underutilization as part of its well-known Employment Situation News Release. A common question we are asked at IPUMS is how to calculate these rates using IPUMS CPS data. The “headline” unemployment figure is known as U-3 and is a straightforward calculation using only the main employment status variable, EMPSTAT. However, the other measures are not quite as simple. Nonetheless, these can be calculated using IPUMS CPS! Using the table below, you can calculate these rates using the public use microdata.

Continue reading…

Malaria Transmission in Context: Linking Health, Census, and Ecological Data

by Yara Ghazal, Ilyana Hohenkirk, Tracy Kugler, and Kelly Searle

Malaria, like many vector-borne diseases, impacts health, economic growth, and society. The burden of malaria incidence and death is concentrated in Sub-Saharan Africa; in 2020, 95% of all malaria cases and 96% of all deaths occurred in Sub-Saharan Africa (WHO, 2022). Malaria impacts not only population health but also the economic growth of these 32 countries. It is estimated that up to 1.3% of economic growth in this region of Africa is slowed each year due to malaria (CCP-JHU, 2015). Understanding malaria transmission is essential to ending its spread and creating a healthier and more prosperous future for developing nations.

The literature on malaria transmission patterns has shown that several environmental factors impact mosquito and parasite vital rates, and thus affect the transmission intensity, seasonality, and geographical distribution of malaria (Castro, 2017). Temperature and precipitation are the primary climate-based factors that influence malaria transmission patterns. Temperature creates geographical constraints for vector and parasite development. Increasing temperatures have been found to shorten mosquito maturation time and increase feeding frequency. However, areas of extremely high temperatures usually yield smaller, less fecund mosquitoes. In parallel, because mosquitoes often breed in pools formed by rainfall and flooding, the frequency, duration, and intensity of precipitation have a significant influence on mosquito populations.

Continue reading…