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The Dangers of Drawing Cohort Profiles From Period Data: A Research Note.

ABSTRACT: Drawing cohort profiles and cohort forecasts from grids of age-period data is common practice in demography. In this research note, we (1) show how demographic measures artificially fluctuate when calculated from the diagonals of age-period rates because of timing and cohort-size bias, (2) estimate the magnitude of these biases, and (3) illustrate how prediction intervals for cohort indicators of mortality may become implausible when drawn from Lee-Carter methods and age-period grids. These biases are surprisingly large, even when the cohort profiles are created from single-age, single-year period data. The danger is that we overinterpret deviations from expected trends that were induced by our own data manipulation.

SUBMITTER: van Raalte AA

PROVIDER: S-EPMC10843689 | biostudies-literature | 2023 Dec

REPOSITORIES: biostudies-literature

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The Dangers of Drawing Cohort Profiles From Period Data: A Research Note.

van Raalte Alyson A AA Basellini Ugofilippo U Camarda Carlo Giovanni CG Nepomuceno Marília R MR Myrskylä Mikko M

Demography 20231201 6

Drawing cohort profiles and cohort forecasts from grids of age-period data is common practice in demography. In this research note, we (1) show how demographic measures artificially fluctuate when calculated from the diagonals of age-period rates because of timing and cohort-size bias, (2) estimate the magnitude of these biases, and (3) illustrate how prediction intervals for cohort indicators of mortality may become implausible when drawn from Lee-Carter methods and age-period grids. These bias ...[more]

PMID: 37965885

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Project description:The chicken microbiota is often analyzed to address questions about the effects of diet or disease on poultry health. To analyze the microbiota, bioinformatic platforms such as QIIME 2 and mothur are used, which incorporate public taxonomic databases such as Greengenes, the ribosomal database project (RDP), and SILVA to assign taxonomies to bacterial sequences. Many chicken microbiota studies continue to incorporate the Greengenes database, which has not been updated since 2013. To determine whether a choice of database could affect results, this study compared the results of bioinformatic analyses obtained using the Greengenes, RDP, and SILVA databases on a cecal luminal microbiome dataset. The QIIME 2 platform was used to process 16S bacterial sequences and assign taxonomies with Greengenes, RDP, and SILVA. Linear discriminant analysis effect size (LEfSe) was performed, allowing for the comparison of taxonomies considered significantly differentially abundant between the three databases. Some notable differences between databases were observed in results, in particular the ability of SILVA database to classify members of the family Lachnospiraceae into separate genera, while these members remained in one group of unclassified Lachnospiraceae through Greengenes and RDP. LEfSe analyses showed that the SILVA database produced more differentially abundant genera, in large part due to the classification of these separate Lachnospiraceae genera. Additionally, the relative abundance of unclassified Lachnospiraceae in SILVA results was significantly lower than in RDP results. Our results show the choice of taxonomic database can influence the results of a microbiota study at the genus level, potentially affecting the interpretation of the results. The use of the SILVA database is recommended over Greengenes in chicken microbiota studies, as more specific classifications at the genus level may provide more accurate interpretations of changes in the microbiota.

Dataset Information

The Dangers of Drawing Cohort Profiles From Period Data: A Research Note.

Publications

The Dangers of Drawing Cohort Profiles From Period Data: A Research Note.

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