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Identification in a regression discontinuity (RD) design hinges on the discontinuity in the probability of treatment when a covariate (assignment variable) exceeds a known threshold. If the assignment variable is measured with error, however, the discontinuity in the relationship between the probability of treatment and the observed mismeasured assignment variable may disappear. Therefore, the presence of measurement error in the assignment variable poses a challenge to treatment effect identification. This chapter provides sufficient conditions to identify the RD treatment effect using the mismeasured assignment variable, the treatment status and the outcome variable. We prove identification separately for discrete and continuous assignment variables and study the properties of various estimation procedures. We illustrate the proposed methods in an empirical application, where we estimate Medicaid takeup and its crowdout effect on private health insurance coverage.

Highly educated and skilled contract workers come from a range of occupations, have different worker characteristics, and work under organizational practices that are precarious in varied ways. Our current understanding of the experience of contract work does not fully encompass this diversity. This chapter focuses on early-career contract workers who contract across national borders – an increasingly prevalent but little understood phenomenon – to broaden our understanding of contract work. I draw on an analysis of 38 in-depth, semi-structured interviews with 30 international and early-career contract workers in the United Nations (UN) system in Geneva, Switzerland. Eight participants were included in follow-up interviews. I find that my participants demonstrate flexibility to their employer. They accept uncertain and short-term contracts, because they hope to secure longer-term positions within the prestigious UN system. Demonstrating flexibility impacts them, their relationships, and has financial implications as participants center the demands of their contracts. At times, participants place limits on how much uncertainty they will bear. This chapter thus illuminates the experiences of an understudied group of contract workers – early-career workers in transnational settings – who fall within the broad umbrella of contract workers. It highlights how even elite workers experience challenges as they engage in contract work.

We study research designs where a binary treatment changes discontinuously at the border between administrative units such as states, counties, or municipalities, creating a treated and a control area. This type of geographically discontinuous treatment assignment can be analyzed in a standard regression discontinuity (RD) framework if the exact geographic location of each unit in the dataset is known. Such data, however, is often unavailable due to privacy considerations or measurement limitations. In the absence of geo-referenced individual-level data, two scenarios can arise depending on what kind of geographic information is available. If researchers have information about each observation’s location within aggregate but small geographic units, a modified RD framework can be applied, where the running variable is treated as discrete instead of continuous. If researchers lack this type of information and instead only have access to the location of units within coarse aggregate geographic units that are too large to be considered in an RD framework, the available coarse geographic information can be used to create a band or buffer around the border, only including in the analysis observations that fall within this band. We characterize each scenario, and also discuss several methodological challenges that are common to all research designs based on geographically discontinuous treatment assignments. We illustrate these issues with an original geographic application that studies the effect of introducing copayments for the use of the Children’s Health Insurance Program in the United States, focusing on the border between Illinois and Wisconsin.

To examine the lived experiences of the biological adult daughters of women with breast cancer.

Family systems theory and phenomenology were used to guide this exploratory, qualitative study. Qualitative data were collected via one-time, semi-structured interviews with adult daughters of women with breast cancer.

Predominant themes included: close mother–daughter relationships, untimely disclosure of information, attentive fathers, optimistic outlooks, and influences on participants’ intimate relationships. Perceived strong familial and intimate relationships prior to breast cancer diagnosis helped ensure that mother–daughter relationships would remain strong, or even improve. Fathers’ attentiveness to mothers was pivotal in determining positive and negative attributes in daughters’ own intimate relationships.

Based on the findings from this study, family scientists and healthcare professionals may have a better understanding of the patients’ young adult daughters’ concerns throughout breast cancer treatment and follow up.

Daughters may be at a loss when their mothers are diagnosed with breast cancer. Healthcare professionals can be equipped to recognize these signs when meeting with patients and families, offer suggestions for family members’ coping, and encourage daughters to consider their own breast cancer risk and screening.

This study will provide a new insight into the experiences of daughters of women with breast cancer, and help family and health professionals understand how to support the relatives of breast cancer patients.