Understanding bias when estimating life expectancy from age at death: a simulation approach applied to Morquio syndrome A

Objective Life expectancy can be estimated accurately from a cohort of individuals born in the same year and followed from birth to death. However, due to the resource-consuming nature of following a cohort prospectively, life expectancy is often assessed based upon retrospective death record reviews. This conventional approach may lead to potentially biased estimates, in particular when estimating life expectancy of rare diseases such as Morquio syndrome A. We investigated the accuracy of life expectancy estimation using death records by simulating the survival of individuals with Morquio syndrome A under four different scenarios. Results When life expectancy was constant during the entire period, using death data did not result in a biased estimate. However, when life expectancy increased over time, as is often expected to be the case in rare diseases, using only death data led to a substantial underestimation of life expectancy. We emphasize that it is therefore crucial to understand how estimates of life expectancy are obtained, to interpret them in an appropriate context, and to assess estimation methods within a sensitivity analysis framework, similar to the simulations performed herein.

Comparative effectiveness and safety of pharmaceuticals assessed in observational studies compared with randomized controlled trials

Background There have been ongoing efforts to understand when and how data from observational studies can be applied to clinical and regulatory decision making. The objective of this review was to assess the comparability of relative treatment effects of pharmaceuticals from observational studies and randomized controlled trials (RCTs). Methods We searched PubMed and Embase for systematic literature reviews published between January 1, 1990, and January 31, 2020, that reported relative treatment effects of pharmaceuticals from both observational studies and RCTs. We extracted pooled relative effect estimates from observational studies and RCTs for each outcome, intervention-comparator, or indication assessed in the reviews. We calculated the ratio of the relative effect estimate from observational studies over that from RCTs, along with the corresponding 95% confidence interval (CI) for each pair of pooled RCT and observational study estimates, and we evaluated the consistency in relative treatment effects. Results Thirty systematic reviews across 7 therapeutic areas were identified from the literature. We analyzed 74 pairs of pooled relative effect estimates from RCTs and observational studies from 29 reviews. There was no statistically significant difference (based on the 95% CI) in relative effect estimates between RCTs and observational studies in 79.7% of pairs. There was an extreme difference (ratio < 0.7 or > 1.43) in 43.2% of pairs, and, in 17.6% of pairs, there was a significant difference and the estimates pointed in opposite directions. Conclusions Overall, our review shows that while there is no significant difference in the relative risk ratios between the majority of RCTs and observational studies compared, there is significant variation in about 20% of comparisons. The source of this variation should be the subject of further inquiry to elucidate how much of the variation is due to differences in patient populations versus biased estimates arising from issues with study design or analytical/statistical methods.

Unmasking the truth: experimental evidence of facemask compliance in Bangladesh, Kenya, and Nigeria during the COVID-19 pandemic

High levels of compliance with public health measures are critical to ensuring a successful response to the COVID-19 pandemic, especially in low and middle-income countries (LMICs). However, most data on compliance are self-reported. Tendency to overreport due to social desirability can yield biased estimates of compliance. We estimate rates of compliance with facemask mandates in Kenya, Nigeria, and Bangladesh using data from phone surveys conducted in March-April 2021. Data on compliance are collected from different survey modules: self-reported compliance (stated) and a list experiment (elicited). We find substantial gaps between stated and elicited rates of facemask wearing for different groups depending on specific country contexts and high levels of overreporting of facemask compliance in self-reported surveys. We observe differences in rates of self-reported facemask wearing among key groups but not using the elicited responses from the list experiment, which suggest that social desirability bias may vary by demographics. Data collected from self-reported surveys may not be reliable to monitor ongoing compliance with public health measures. Moreover, elicited compliance rates indicate levels of mask wearing are likely much lower than those estimated using self-reported data.

What You Need to Know When Estimating Impact Functions with Panel Data for Demographic Research

The estimation of impact functions – that is the time-varying causal effect of a dichotomous treatment (e.g., marriage, divorce, parenthood) on outcomes (e.g., earnings, well-being, health) – has become a standard procedure in demographic applications. The basic methodology of estimating impact functions with panel data and fixed-effects regressions is now widely known. However, many researchers may not be fully aware of the methodological subtleties of the approach, which may lead to biased estimates of the impact function. In this paper, we highlight potential pitfalls and provide guidance on how to avoid these in practice. We demonstrate these issues with exemplary analyses, using data from the German Family Panel (pairfam) study and estimating the effect of motherhood on life satisfaction. * This article belongs to a special issue on “Identification of causal mechanisms in demographic research: The contribution of panel data”.

Blue Cod, Parapercis Colias, Maturity, Fecundity, Sex Change, and Potential Drivers of Sex Ratio in The Marlborough Sounds

<p>Blue cod, Parapercis colias (Pinguipedidae), are widely considered to be the most important recreational finfish species in the South Island. However, blue cod have been declining in abundance in the Marlborough Sounds for many years, and currently, sex ratios are highly male- biased. Blue cod are believed to be a socially structured hermaphroditic species whose populations are prone to local depletion. A potting survey in the Marlborough Sounds was carried out by NIWA in 2013, and along with environmental measurements, 3247 blue cod were measured, weighed, sexed, and stage of sexual maturity was classified macroscopically at sea. Gonads from a subsample of these fish were removed and preserved. In Chapter Two, the preserved gonads were processed histologically and a species-specific histological maturity key was developed. Histological and macroscopic maturity classifications and length-at-maturity estimates were compared. Additionally, estimates of spawning frequency and batch fecundity were made using histological and gravimetric methods. In Chapter Three, possible drivers of sex ratio were investigated using the survey data. Density, large male influence, and environmental factors were considered. In Chapter Four, the feasibility of using digital imaging software to age blue cod otoliths was investigated using the OtolithM application in ImagePro Premier. There was poor agreement between macroscopic and histological maturity classifications (20%, overall). Macroscopic methods overestimated the proportion of mature fish at length in the larger sample, which led to biased length-at-50% maturity (L₅₀) estimates. Macroscopic L₅₀ estimates differed markedly from histology estimates. Using histological data, male L₅₀ was 26 cm TL. Histology indicated that there was no length at which 100% of females were mature. Therefore, a three-parameter capped logistic model was used. Histologically, female L₅₀ was 23.6 cm TL, and the Cap was 0.78, indicating the proportion of mature females reached an asymptote at 0.78. Spawning frequency was 4.6 days, and mean relative batch fecundity was 6.5 hydrated oocytes per gram body weight (SD = 3.3). Hermaphroditism was confirmed for blue cod and was macroscopically identifiable. The analyses in Chapter Three indicated that density had some effect on sex ratio, and large males influenced local sex ratios. Finally, the imaging software could not accurately estimate age compared to an expert reader, and it produced highly variable age estimates. This research found that the macroscopic maturity classifications for blue cod were inaccurate, and revision of the macroscopic key is suggested. The biased estimates of L₅₀ from macroscopic data could lead to biased estimates of spawning stock biomass (SSB). Batch fecundity was markedly lower than the previously reported estimates. The finding of a macroscopically identifiable hermaphroditic stage suggested that ‘hermaphrodite’ should be added as a sex class in the macroscopic key. From the GLM in Chapter Three, in more dense populations, the proportion of males increased. This may have been from changes to male mating strategies, or density may influence the occurrence of primary and secondary males. Finally, areas with males > 45 cm TL had a higher proportion of females, suggesting that large males should be protected in order to help balance sex ratios.</p>

Blue Cod, Parapercis Colias, Maturity, Fecundity, Sex Change, and Potential Drivers of Sex Ratio in The Marlborough Sounds

<p>Blue cod, Parapercis colias (Pinguipedidae), are widely considered to be the most important recreational finfish species in the South Island. However, blue cod have been declining in abundance in the Marlborough Sounds for many years, and currently, sex ratios are highly male- biased. Blue cod are believed to be a socially structured hermaphroditic species whose populations are prone to local depletion. A potting survey in the Marlborough Sounds was carried out by NIWA in 2013, and along with environmental measurements, 3247 blue cod were measured, weighed, sexed, and stage of sexual maturity was classified macroscopically at sea. Gonads from a subsample of these fish were removed and preserved. In Chapter Two, the preserved gonads were processed histologically and a species-specific histological maturity key was developed. Histological and macroscopic maturity classifications and length-at-maturity estimates were compared. Additionally, estimates of spawning frequency and batch fecundity were made using histological and gravimetric methods. In Chapter Three, possible drivers of sex ratio were investigated using the survey data. Density, large male influence, and environmental factors were considered. In Chapter Four, the feasibility of using digital imaging software to age blue cod otoliths was investigated using the OtolithM application in ImagePro Premier. There was poor agreement between macroscopic and histological maturity classifications (20%, overall). Macroscopic methods overestimated the proportion of mature fish at length in the larger sample, which led to biased length-at-50% maturity (L₅₀) estimates. Macroscopic L₅₀ estimates differed markedly from histology estimates. Using histological data, male L₅₀ was 26 cm TL. Histology indicated that there was no length at which 100% of females were mature. Therefore, a three-parameter capped logistic model was used. Histologically, female L₅₀ was 23.6 cm TL, and the Cap was 0.78, indicating the proportion of mature females reached an asymptote at 0.78. Spawning frequency was 4.6 days, and mean relative batch fecundity was 6.5 hydrated oocytes per gram body weight (SD = 3.3). Hermaphroditism was confirmed for blue cod and was macroscopically identifiable. The analyses in Chapter Three indicated that density had some effect on sex ratio, and large males influenced local sex ratios. Finally, the imaging software could not accurately estimate age compared to an expert reader, and it produced highly variable age estimates. This research found that the macroscopic maturity classifications for blue cod were inaccurate, and revision of the macroscopic key is suggested. The biased estimates of L₅₀ from macroscopic data could lead to biased estimates of spawning stock biomass (SSB). Batch fecundity was markedly lower than the previously reported estimates. The finding of a macroscopically identifiable hermaphroditic stage suggested that ‘hermaphrodite’ should be added as a sex class in the macroscopic key. From the GLM in Chapter Three, in more dense populations, the proportion of males increased. This may have been from changes to male mating strategies, or density may influence the occurrence of primary and secondary males. Finally, areas with males > 45 cm TL had a higher proportion of females, suggesting that large males should be protected in order to help balance sex ratios.</p>

When a Truly Positive Correlation Turns Negative: How Different Approaches to Model Hierarchically Structured Constructs Affect Estimated Correlations to Covariates

Many constructs in personality psychology assume a hierarchical structure positing a general factor along with several narrower subdimensions or facets. Different approaches are commonly used to model such a structure, including higher-order factor models, bifactor models, single-factor models based on the responses on the observed items, and single-factor models based on parcels computed from the mean observed scores on the subdimensions. The present article investigates the consequences of adopting a certain approach for the validity of conclusions derived from the thereby obtained correlation of the most general factor to a covariate. Any of the considered approaches may closely approximate the true correlation when its underlying assumptions are met or when model misspecifications only pertain to the measurement model of the hierarchical construct. However, when misspecifications involve nonmodeled covariances between parts of the hierarchically structured construct and the covariate, higher-order models, single-factor representations, and facet-parcel approaches can yield severely biased estimates sometimes grossly misrepresenting the true correlation and even incurring sign changes. In contrast, a bifactor approach proved to be most robust and to provide rather unbiased results under all conditions. The implications are discussed and recommendations are provided.

Non-iterative Conditional Pairwise Estimation for the Rating Scale Model

We investigate two non-iterative estimation procedures for Rasch models, the pair-wise estimation procedure (PAIR) and the Eigenvector method (EVM), and identify theoretical issues with EVM for rating scale model (RSM) threshold estimation. We develop a new procedure to resolve these issues—the conditional pairwise adjacent thresholds procedure (CPAT)—and test the methods using a large number of simulated datasets to compare the estimates against known generating parameters. We find support for our hypotheses, in particular that EVM threshold estimates suffer from theoretical issues which lead to biased estimates and that CPAT represents a means of resolving these issues. These findings are both statistically significant ( p < .001) and of a large effect size. We conclude that CPAT deserves serious consideration as a conditional, computationally efficient approach to Rasch parameter estimation for the RSM. CPAT has particular potential for use in contexts where computational load may be an issue, such as systems with multiple online algorithms and large test banks with sparse data designs.