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Relevant bibliographies by topics / Multiple ancillaries / Journal articles

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Journal articles on the topic 'Multiple ancillaries'

Author: Grafiati

Published: 7 June 2025

Last updated: 2 August 2025

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1

Igcalinos, Jennifer, and Jubert Gulo. "The Tales of Mathematics Teachers with Multiple Ancillaries: A Phenomenology." Psychology and Education: A Multidisciplinary Journal 30, no. 2 (2025): 395–414. https://doi.org/10.5281/zenodo.14604123.

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This phenomenology study aimed to explore and understand the lived experiences of mathematics teachers with multiple ancillaries. Using snowball sampling, the participating 14 mathematics teachers with multiple ancillaries were identified. All of them participated in the in-depth interviews. Results revealed the experiences of the participants: had to catch up lessons; had difficulty to divide one’s time; gained additional experiential knowledge/learning; and had developed confidence and other skills. In response to the challenges, they have faced: prioritizing and streamlining tasks; ut

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2

Villavicencio, Camila Alejandra, Alberto Franco-Akel, Regina Belokovskaya, et al. "Severe Hyperbilirubinemia Associated With Thyrotoxicosis: Importance of Early Recognition." Journal of the Endocrine Society 5, Supplement_1 (2021): A952—A953. http://dx.doi.org/10.1210/jendso/bvab048.1946.

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Abstract Thyroid storm (TS) is a rare and life-threatening condition due to a profound hypermetabolic state, leading to decompensation of homeostasis. It is commonly associated with a precipitating factor such as surgery, trauma, or infection. Occasionally, the clinical presentation may be non-specific, thus causing a potential delay in diagnosis. This could be problematic due to the condition’s high mortality rate, especially if not recognized early. Thyrotoxic jaundice presenting with a pattern of cholestatic hyperbilirubinemia (HBR) has been reported in the literature, although uncommon. We

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3

Brown, Lawrence D. "An Ancillarity Paradox Which Appears in Multiple Linear Regression." Annals of Statistics 18, no. 2 (1990): 471–93. http://dx.doi.org/10.1214/aos/1176347602.

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4

Berger, James. "Discussion: An Ancillarity Paradox which Appears in Multiple Linear Regression." Annals of Statistics 18, no. 2 (1990): 493–96. http://dx.doi.org/10.1214/aos/1176347603.

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5

Casella, George. "Discussion: An Ancillarity Paradox which Appears in Multiple Linear Regression." Annals of Statistics 18, no. 2 (1990): 497–500. http://dx.doi.org/10.1214/aos/1176347604.

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6

Copas, J. B. "Discussion: An Ancillarity Paradox which Appears in Multiple Linear Regression." Annals of Statistics 18, no. 2 (1990): 500–502. http://dx.doi.org/10.1214/aos/1176347605.

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7

Efron, B. "Discussion: An Ancillarity Paradox which Appears in Multiple Linear Regression." Annals of Statistics 18, no. 2 (1990): 502–3. http://dx.doi.org/10.1214/aos/1176347606.

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8

Fraser, D. A. S., and N. Reid. "Discussion: An Ancillarity Paradox which Appears in Multiple Linear Regression." Annals of Statistics 18, no. 2 (1990): 503–7. http://dx.doi.org/10.1214/aos/1176347607.

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9

Gleser, Leon Jay. "Discussion: An Ancillarity Paradox which Appears in Multiple Linear Regression." Annals of Statistics 18, no. 2 (1990): 507–13. http://dx.doi.org/10.1214/aos/1176347608.

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10

Hill, B. M. "Discussion: An Ancillarity Paradox which Appears in Multiple Linear Regression." Annals of Statistics 18, no. 2 (1990): 513–23. http://dx.doi.org/10.1214/aos/1176347609.

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11

Johnstone, Iain M. "Discussion: An Ancillarity Paradox which Appears in Multiple Linear Regression." Annals of Statistics 18, no. 2 (1990): 523–25. http://dx.doi.org/10.1214/aos/1176347610.

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12

Lu, Kun-Liang. "Discussion: An Ancillarity Paradox which Appears in Multiple Linear Regression." Annals of Statistics 18, no. 2 (1990): 525–28. http://dx.doi.org/10.1214/aos/1176347611.

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13

Morris, C. N. "Discussion: An Ancillarity Paradox which Appears in Multiple Linear Regression." Annals of Statistics 18, no. 2 (1990): 528–30. http://dx.doi.org/10.1214/aos/1176347612.

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14

Stein, Charles. "Discussion: An Ancillarity Paradox which Appears in Multiple Linear Regression." Annals of Statistics 18, no. 2 (1990): 530–33. http://dx.doi.org/10.1214/aos/1176347613.

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15

Brown, Lawrence D. "Rejoinder: An Ancillarity Paradox which Appears in Multiple Linear Regression." Annals of Statistics 18, no. 2 (1990): 533–38. http://dx.doi.org/10.1214/aos/1176347614.

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16

Kolbeinsson, Arinbjörn, Naman Shukla, Akhil Gupta, Lavanya Marla, and Kartik Yellepeddi. "Galactic Air Improves Ancillary Revenues with Dynamic Personalized Pricing." INFORMS Journal on Applied Analytics, January 13, 2022. http://dx.doi.org/10.1287/inte.2021.1105.

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Ancillaries are a rapidly growing source of revenue for airlines, yet their prices are currently statically determined using rules of thumb and are matched only to the average customer or to customer groups. Offering ancillaries at dynamic and personalized prices based on flight characteristics and customer needs could greatly improve airline revenue and customer satisfaction. Through a start-up (Deepair) that builds and deploys novel machine learning techniques to introduce such dynamically priced ancillaries to airlines, we partnered with a major European airline, Galactic Air (pseudonym), t

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17

Jr, Rogelio O. Rabe, and Remigilda D. Gallardo. "Travails of Elementary Teachers: Handling Multiple Ancillary Functions." International Journal of Innovative Science and Research Technology, March 31, 2025, 1481–83. https://doi.org/10.38124/ijisrt/25mar1155.

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This study seeks to provide a better understanding of the travails and struggles have on doing ancillary services aside from the daily six hours of teaching loads. This study employed phenomenological research design using in -depth interview (IDI) of ten participants through purposive sampling. In analyzing the lived experiences of the elementary teachers on handling multiple ancillary functions, the researcher was able to identify four major themes. These are joyful acceptance, sense of fulfillment, and struggles in the implementation. Further, there were also three (3) subthemes that emerge

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18

Battey, H. S., and D. R. Cox. "Missing observations in regression: a conditional approach." Royal Society Open Science 10, no. 2 (2023). http://dx.doi.org/10.1098/rsos.220267.

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This note presents an alternative to multiple imputation and other approaches to regression analysis in the presence of missing covariate data. Our recommendation, based on factorial and fractional factorial arrangements, is more faithful to ancillarity considerations of regression analysis and involves assessing the sensitivity of inference on each regression parameter to missingness in each of the explanatory variables. The ideas are illustrated on a medical example concerned with the success of hematopoietic stem cell transplantation in children, and on a sociological example concerned with

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