TY - JOUR A1 - Lenhard, Alexandra A1 - Minten, Marie-Pierre A1 - Lenhard, Wolfgang T1 - When biology takes over: TV formats like The Bachelor and The Bachelorette confirm evolutionary theories of partner selection JF - Frontiers in Psychology N2 - Introduction: In this study, we investigated the impact of age on mate selection preferences in males and females, and explored how the formation and duration of committed relationships depend on the sex of the person making the selection. Methods: To this end, we utilized data from the television dating shows The Bachelor and The Bachelorette. In these programs, either a single man (“bachelor”) or a woman (“bachelorette”) has the opportunity to select a potential long-term partner from a pool of candidates. Our analysis encompassed a total of n = 169 seasons from 23 different countries, beginning with the first airing in 2002. Results: We found that the likelihood of the final couple continuing their relationship beyond the broadcast was higher in The Bachelorette than in The Bachelor, although the duration of these relationships was not significantly influenced by the type of show. On average, women were younger, both when selecting their partner and when being chosen. However, men exhibited a greater preference for larger age differences than women. Furthermore, the age of the chosen male partners significantly increased with the age of the “bachelorettes,” whereas “bachelors” consistently favored women around 25.5 years old, regardless of their own age. Discussion: We discuss these findings within the context of parental investment theory and sexual strategies theory. KW - mating strategies KW - parental investment theory KW - sex differences KW - relationship duration KW - Cox proportional regression analysis Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-325717 SN - 1664-1078 VL - 14 ER - TY - JOUR A1 - Lenhard, Alexandra A1 - Lenhard, Wolfgang A1 - Gary, Sebastian T1 - Continuous norming of psychometric tests: A simulation study of parametric and semi-parametric approaches JF - PLoS ONE N2 - Continuous norming methods have seldom been subjected to scientific review. In this simulation study, we compared parametric with semi-parametric continuous norming methods in psychometric tests by constructing a fictitious population model within which a latent ability increases with age across seven age groups. We drew samples of different sizes (n = 50, 75, 100, 150, 250, 500 and 1,000 per age group) and simulated the results of an easy, medium, and difficult test scale based on Item Response Theory (IRT). We subjected the resulting data to different continuous norming methods and compared the data fit under the different test conditions with a representative cross-validation dataset of n = 10,000 per age group. The most significant differences were found in suboptimal (i.e., too easy or too difficult) test scales and in ability levels that were far from the population mean. We discuss the results with regard to the selection of the appropriate modeling techniques in psychometric test construction, the required sample sizes, and the requirement to report appropriate quantitative and qualitative test quality criteria for continuous norming methods in test manuals. KW - statistical models KW - simulation and modeling KW - psychometrics KW - age groups KW - skewness KW - normal distribution KW - polynomials KW - statistical distributions Y1 - 2019 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-200480 VL - 14 IS - 9 ER - TY - JOUR A1 - Gary, Sebastian A1 - Lenhard, Wolfgang A1 - Lenhard, Alexandra T1 - Modelling norm scores with the cNORM package in R JF - Psych N2 - In this article, we explain and demonstrate how to model norm scores with the cNORM package in R. This package is designed specifically to determine norm scores when the latent ability to be measured covaries with age or other explanatory variables such as grade level. The mathematical method used in this package draws on polynomial regression to model a three-dimensional hyperplane that smoothly and continuously captures the relation between raw scores, norm scores and the explanatory variable. By doing so, it overcomes the typical problems of classical norming methods, such as overly large age intervals, missing norm scores, large amounts of sampling error in the subsamples or huge requirements with regard to the sample size. After a brief introduction to the mathematics of the model, we describe the individual methods of the package. We close the article with a practical example using data from a real reading comprehension test. KW - regression-based norming KW - continuous norming KW - inferential norming KW - data smoothing KW - curve fitting KW - percentile estimation Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-284143 SN - 2624-8611 VL - 3 IS - 3 SP - 501 EP - 521 ER -