Sample Size Determination for Regression Models Using Monte Carlo Methods in \u3cb\u3eR\u3c/b\u3e

A common question asked by researchers using regression models is, What sample size is needed for my study? While there are formulae to estimate sample sizes, their assumptions are often not met in the collected data. A more realistic approach to sample size determination requires more information such as the model of interest, strength of the relations among the variables, and any data quirks (e.g., missing data, variable distributions, variable reliability). Such information can only be incorporated into sample size determination methods that use Monte Carlo (MC) methods. The purpose of this article is to demonstrate how to use a MC study to decide on sample size for a regression analysis using both power and parameter accuracy perspectives. Using multiple regression examples with and without data quirks, I demonstrate the MC analyses with the R statistical programming language. Accessed 22,856 times on https://pareonline.net from August 23, 2014 to December 31, 2019. For downloads from January 1, 2020 forward, please click on the PlumX Metrics link to the right

Factor Analysis using R

R (R Development Core Team, 2011) is a very powerful tool to analyze data, that is gaining in popularity due to its costs (its free) and flexibility (its open-source). This article gives a general introduction to using R (i.e., loading the program, using functions, importing data). Then, using data from Canivez, Konold, Collins, and Wilson (2009), this article walks the user through how to use the program to conduct factor analysis, from both an exploratory and confirmatory approach. Accessed 36,214 times on https://pareonline.net from February 25, 2013 to December 31, 2019. For downloads from January 1, 2020 forward, please click on the PlumX Metrics link to the right

Tutorial on Using Regression Models with Count Outcomes using \u3cb\u3eR\u3c/b\u3e

Education researchers often study count variables, such as times a student reached a goal, discipline referrals, and absences. Most researchers that study these variables use typical regression methods (i.e., ordinary least-squares) either with or without transforming the count variables. In either case, using typical regression for count data can produce parameter estimates that are biased, thus diminishing any inferences made from such data. As count-variable regression models are seldom taught in training programs, we present a tutorial to help educational researchers use such methods in their own research. We demonstrate analyzing and interpreting count data using Poisson, negative binomial, zero-inflated Poisson, and zero-inflated negative binomial regression models. The count regression methods are introduced through an example using the number of times students skipped class. The data for this example are freely available and the R syntax used run the example analyses are included in the Appendix. Accessed 16,559 times on https://pareonline.net from February 02, 2016 to December 31, 2019. For downloads from January 1, 2020 forward, please click on the PlumX Metrics link to the right

Measuring Personality in Wave I of the National Longitudinal Study of Adolescent Health

The researchers sought to develop a personality measure from items in Wave I of the National Longitudinal Study of Adolescent Health. The study found 13 items from three dimensions of personality (neuroticism, extroversion, and conscientiousness), and then examined the factor structure and internal consistency of each of the three dimensions. Within each personality dimension, the items showed a unidimensional factor structure and internal consistency estimates of the summed similar to scores from NEO Personality Inventories. The results can be used to further examine how child/adolescent personality is related to multiple mental and physical health outcomes in the Add Health database

The ALTCRISS project on board the International Space Station

The Altcriss project aims to perform a long term survey of the radiation environment on board the International Space Station. Measurements are being performed with active and passive devices in different locations and orientations of the Russian segment of the station. The goal is to perform a detailed evaluation of the differences in particle fluence and nuclear composition due to different shielding material and attitude of the station. The Sileye-3/Alteino detector is used to identify nuclei up to Iron in the energy range above 60 MeV/n. Several passive dosimeters (TLDs, CR39) are also placed in the same location of Sileye-3 detector. Polyethylene shielding is periodically interposed in front of the detectors to evaluate the effectiveness of shielding on the nuclear component of the cosmic radiation. The project was submitted to ESA in reply to the AO in the Life and Physical Science of 2004 and data taking began in December 2005. Dosimeters and data cards are rotated every six months: up to now three launches of dosimeters and data cards have been performed and have been returned with the end of expedition 12 and 13.Comment: Accepted for publication on Advances in Space Research http://dx.doi.org/10.1016/j.asr.2007.04.03

Bayesian Fit of Exclusive b→sℓˉℓb \to s \bar\ell\ell Decays: The Standard Model Operator Basis

We perform a model-independent fit of the short-distance couplings $C_{7,9,10}$ within the Standard Model set of $b\to s\gamma$ and $b\to s\bar\ell\ell$ operators. Our analysis of $B \to K^* \gamma$, $B \to K^{(*)} \bar\ell\ell$ and $B_s \to \bar\mu\mu$ decays is the first to harness the full power of the Bayesian approach: all major sources of theory uncertainty explicitly enter as nuisance parameters. Exploiting the latest measurements, the fit reveals a flipped-sign solution in addition to a Standard-Model-like solution for the couplings $C_i$. Each solution contains about half of the posterior probability, and both have nearly equal goodness of fit. The Standard Model prediction is close to the best-fit point. No New Physics contributions are necessary to describe the current data. Benefitting from the improved posterior knowledge of the nuisance parameters, we predict ranges for currently unmeasured, optimized observables in the angular distributions of $B\to K^*(\to K\pi)\,\bar\ell\ell$.Comment: 42 pages, 8 figures; v2: Using new lattice input for f_Bs, considering Bs-mixing effects in BR[B_s->ll]. Main results and conclusion unchanged, matches journal versio

Cornering New Physics in b --> s Transitions

We derive constraints on Wilson coefficients of dimension-six effective operators probing the b --> s transition, using recent improved measurements of the rare decays Bs --> mu+mu-, B --> K mu+mu- and B --> K* mu+mu- and including all relevant observables in inclusive and exclusive decays. We consider operators present in the SM as well as their chirality-flipped counterparts and scalar operators. We find good agreement with the SM expectations. Compared to the situation before winter 2012, we find significantly more stringent constraints on the chirality-flipped coefficients due to complementary constraints from B --> K mu+mu- and B --> K* mu+mu- and due to the LHCb measurement of the angular observable S_3 in the latter decay. We also list the full set of observables sensitive to new physics in the low recoil region of B --> K* mu+mu-.Comment: 18 pages, 6 figures, 4 tables. v3: typos correcte

Cosmic ray LET spectra and doses on board Cosmos-2044 biosatellite

Results of the experiments on board Cosmos-2044 (Biosatellite 9) are presented. Various nuclear track detectors (NTD) (dielectric, AgCl-based, nuclear emulsions) were used to obtain the Linear Energy Transfer (LET) spectra inside and outside the satellite. The spectra from the different NTDs have proved to be in general agreement. The results of LET spectra calculations using two different models are also presented. The resultant LET distributions are used to calculate the absorbed and equivalent doses and the orbit-averaged quality factors (QF) of the cosmic rays (CR). Absorbed dose rates inside (approximately 20 g cm (exp -2) shielding) and outside (1 g cm(exp -2) the spacecraft, omitting electrons, were found to be 4.8 and 8.6 mrad d (exp -1), respectively, while the corresponding equivalent doses were 8.8 and 19.7 mrem d(exp -1). The effects of the flight parameters on the total fluence of, and on the dose from the CR particles are analyzed. Integral dose distributions of the detected particles are also determined. The LET values which separate absorbed and equivalent doses into 50% intervals are estimated. The CR-39 dielectric NTD is shown to detect 20-30% of the absorbed dose and 60-70% of the equivalent dose in the Cosmos-2044 orbit. The influence of solar activity phase on the magnitude of CR flux is discussed