Matching Items (20)
DescriptionDuring the Third Wave of Democratization, the United States has influenced many different cultures through politics and social interests. The way in which this has occurred is through their marketing and advertising. Many companies are the reason that the United States is a super power today.
ContributorsNebeker, Garrett Albert (Author) / Wilson, Jeffrey (Thesis director) / Reiser, Mark (Committee member) / Barrett, The Honors College (Contributor) / Department of Finance (Contributor) / W. P. Carey School of Business (Contributor)
Created2015-05
Description
Objective: To assess and quantify the effect of state’s price transparency regulations (hereafter, PTR) on healthcare pricing.
Data Sources: I use the Healthcare Cost and Utilization Project’s Nationwide Inpatient Sample (NIS) from 2000 to 2011. The NIS is a 20% sample of all inpatient claims. The Manhattan Institute supplied data on the availability of health savings accounts in each state. State PTR implementation dates were gathered by Hans Christensen, Eric Floyd, and Mark Maffett of University of Chicago’s Booth School of Business by contacting the health department, hospital association, or website controller in each state.
Study Design: The NIS data was collapsed by procedure, hospital, and year providing averages for the dependent variable, Cost, and a host of covariates. Cost is a product of Total Charges within the NIS and the hospital’s Cost to Charge ratio. A new binary variable, PTR, was defined as ‘0’ if the year was strictly less than the disclosure website’s implementation date, ‘1’ for afterwards, and missing for the year of implementation. Then, using multivariate OLS regression with fixed effect modeling, the change in cost from before to after the year of implementation is estimated.
Principal Findings: The analysis estimates the effect of PTR to decrease the average cost per procedure by 7%. Specifications identify within state, within hospital, and within procedure variation, and reports that 78% of the cost decrease is due to within-hospital, within-procedure price discounts. An additional model includes the interaction of PTR with the prevalence of health savings accounts (hereafter, HSAs) and procedure electivity. The results show that PTR lowers costs by an additional 3 percent with each additional 10 percentage point increase in the availability of HSAs. In contrast, the cost reductions from PTR were much smaller for procedures more frequently coded as elective.
Conclusions: The study concludes price transparency regulations can lead to a decrease in a procedure’s costs on average, primarily through price discounts and slightly through lower cost procedures, but not due to patients moving to cheaper hospitals. This implies that hospitals are taking initiative and lowering prices as the competition’s prices become publically available suggesting that hospitals – not patients – are the biggest users of price transparency websites. Hospitals are also finding some ways to provide cheaper alternatives to more expensive procedures. State regulators should evaluate if a better metric other than charge prices, such as expected out-of-pocket payments, would evoke greater patient participation. Furthermore, states with higher prevalence of HSAs experience greater effects of PTR as expected since patients with HSAs have greater incentives to lower their costs. Patients should expect a shift towards plans that offer these types of savings accounts since they’ve shown to have a reduction of health costs on average per procedure in states with higher prevalence of HSAs.
Data Sources: I use the Healthcare Cost and Utilization Project’s Nationwide Inpatient Sample (NIS) from 2000 to 2011. The NIS is a 20% sample of all inpatient claims. The Manhattan Institute supplied data on the availability of health savings accounts in each state. State PTR implementation dates were gathered by Hans Christensen, Eric Floyd, and Mark Maffett of University of Chicago’s Booth School of Business by contacting the health department, hospital association, or website controller in each state.
Study Design: The NIS data was collapsed by procedure, hospital, and year providing averages for the dependent variable, Cost, and a host of covariates. Cost is a product of Total Charges within the NIS and the hospital’s Cost to Charge ratio. A new binary variable, PTR, was defined as ‘0’ if the year was strictly less than the disclosure website’s implementation date, ‘1’ for afterwards, and missing for the year of implementation. Then, using multivariate OLS regression with fixed effect modeling, the change in cost from before to after the year of implementation is estimated.
Principal Findings: The analysis estimates the effect of PTR to decrease the average cost per procedure by 7%. Specifications identify within state, within hospital, and within procedure variation, and reports that 78% of the cost decrease is due to within-hospital, within-procedure price discounts. An additional model includes the interaction of PTR with the prevalence of health savings accounts (hereafter, HSAs) and procedure electivity. The results show that PTR lowers costs by an additional 3 percent with each additional 10 percentage point increase in the availability of HSAs. In contrast, the cost reductions from PTR were much smaller for procedures more frequently coded as elective.
Conclusions: The study concludes price transparency regulations can lead to a decrease in a procedure’s costs on average, primarily through price discounts and slightly through lower cost procedures, but not due to patients moving to cheaper hospitals. This implies that hospitals are taking initiative and lowering prices as the competition’s prices become publically available suggesting that hospitals – not patients – are the biggest users of price transparency websites. Hospitals are also finding some ways to provide cheaper alternatives to more expensive procedures. State regulators should evaluate if a better metric other than charge prices, such as expected out-of-pocket payments, would evoke greater patient participation. Furthermore, states with higher prevalence of HSAs experience greater effects of PTR as expected since patients with HSAs have greater incentives to lower their costs. Patients should expect a shift towards plans that offer these types of savings accounts since they’ve shown to have a reduction of health costs on average per procedure in states with higher prevalence of HSAs.
ContributorsSabol, Joshua Lawrence (Author) / Reiser, Mark (Thesis director) / Ketcham, Jonathan (Committee member) / Dassanayake, Maduranga (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Department of Supply Chain Management (Contributor)
Created2015-05
Description
We used sex, observed parenting quality at 18 months, and three variants of the catechol-O-methyltransferase gene (Val[superscript 158]Met [rs4680], intron1 [rs737865], and 3′-untranslated region [rs165599]) to predict mothers' reports of inhibitory and attentional control (assessed at 42, 54, 72, and 84 months) and internalizing symptoms (assessed at 24, 30, 42, 48, and 54 months) in a sample of 146 children (79 male). Although the pattern for all three variants was very similar, Val[superscript 158]Met explained more variance in both outcomes than did intron1, the 3′-untranslated region, or a haplotype that combined all three catechol-O-methyltransferase variants. In separate models, there were significant three-way interactions among each of the variants, parenting, and sex, predicting the intercepts of inhibitory control and internalizing symptoms. Results suggested that Val[superscript 158]Met indexes plasticity, although this effect was moderated by sex. Parenting was positively associated with inhibitory control for methionine–methionine boys and for valine–valine/valine–methionine girls, and was negatively associated with internalizing symptoms for methionine–methionine boys. Using the “regions of significance” technique, genetic differences in inhibitory control were found for children exposed to high-quality parenting, whereas genetic differences in internalizing were found for children exposed to low-quality parenting. These findings provide evidence in support of testing for differential susceptibility across multiple outcomes.
ContributorsSulik, Michael (Author) / Eisenberg, Nancy (Author) / Spinrad, Tracy (Author) / Lemery, Kathryn (Author) / Swann, Gregory (Author) / Silva, Kassondra (Author) / Reiser, Mark (Author) / Stover, Daryn (Author) / Verrelli, Brian (Author) / College of Liberal Arts and Sciences (Contributor) / Department of Psychology (Contributor) / Sanford School of Social and Family Dynamics (Contributor) / School of Mathematical and Statistical Sciences (Contributor)
Created2015-08-01
Description
The purpose of this study was to examine whether dispositional sadness predicted children's prosocial behavior and if sympathy mediated this relation. Constructs were measured when children (n = 256 at time 1) were 18, 30, and 42 months old. Mothers and non-parental caregivers rated children's sadness; mothers, caregivers, and fathers rated children's prosocial behavior; sympathy (concern and hypothesis testing) and prosocial behavior (indirect and direct, as well as verbal at older ages) were assessed with a task in which the experimenter feigned injury. In a panel path analysis, 30-month dispositional sadness predicted marginally higher 42-month sympathy; in addition, 30-month sympathy predicted 42-month sadness. Moreover, when controlling for prior levels of prosocial behavior, 30-month sympathy significantly predicted reported and observed prosocial behavior at 42 months. Sympathy did not mediate the relation between sadness and prosocial behavior (either reported or observed).
ContributorsEdwards, Alison (Author) / Eisenberg, Nancy (Author) / Spinrad, Tracy (Author) / Reiser, Mark (Author) / Wilkens, Natalie (Author) / Liew, Jeffrey (Author) / College of Liberal Arts and Sciences (Contributor) / Department of Psychology (Contributor) / Sanford School of Social and Family Dynamics (Contributor) / School of Mathematical and Statistical Sciences (Contributor)
Created2015-01-01
Description
We seek a comprehensive measurement for the economic prosperity of persons with disabilities. We survey the current literature and identify the major economic indicators used to describe the socioeconomic standing of persons with disabilities. We then develop a methodology for constructing a statistically valid composite index of these indicators, and build this index using data from the 2014 American Community Survey. Finally, we provide context for further use and development of the index and describe an example application of the index in practice.
ContributorsTheisen, Ryan (Co-author) / Helms, Tyler (Co-author) / Lewis, Paul (Thesis director) / Reiser, Mark (Committee member) / Economics Program in CLAS (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / School of Politics and Global Studies (Contributor) / Barrett, The Honors College (Contributor)
Created2017-05
Description
Longitudinal data involving multiple subjects is quite popular in medical and social science areas. I consider generalized linear mixed models (GLMMs) applied to such longitudinal data, and the optimal design searching problem under such models. In this case, based on optimal design theory, the optimality criteria depend on the estimated parameters, which leads to local optimality. Moreover, the information matrix under a GLMM doesn't have a closed-form expression. My dissertation includes three topics related to this design problem. The first part is searching for locally optimal designs under GLMMs with longitudinal data. I apply penalized quasi-likelihood (PQL) method to approximate the information matrix and compare several approximations to show the superiority of PQL over other approximations. Under different local parameters and design restrictions, locally D- and A- optimal designs are constructed based on the approximation. An interesting finding is that locally optimal designs sometimes apply different designs to different subjects. Finally, the robustness of these locally optimal designs is discussed. In the second part, an unknown observational covariate is added to the previous model. With an unknown observational variable in the experiment, expected optimality criteria are considered. Under different assumptions of the unknown variable and parameter settings, locally optimal designs are constructed and discussed. In the last part, Bayesian optimal designs are considered under logistic mixed models. Considering different priors of the local parameters, Bayesian optimal designs are generated. Bayesian design under such a model is usually expensive in time. The running time in this dissertation is optimized to an acceptable amount with accurate results. I also discuss the robustness of these Bayesian optimal designs, which is the motivation of applying such an approach.
ContributorsShi, Yao (Author) / Stufken, John (Thesis advisor) / Kao, Ming-Hung (Thesis advisor) / Lan, Shiwei (Committee member) / Pan, Rong (Committee member) / Reiser, Mark (Committee member) / Arizona State University (Publisher)
Created2022
Description
Goodness-of-fit test is a hypothesis test used to test whether a given model fit the data well. It is extremely difficult to find a universal goodness-of-fit test that can test all types of statistical models. Moreover, traditional Pearson’s chi-square goodness-of-fit test is sometimes considered to be an omnibus test but not a directional test so it is hard to find the source of poor fit when the null hypothesis is rejected and it will lose its validity and effectiveness in some of the special conditions. Sparseness is such an abnormal condition. One effective way to overcome the adverse effects of sparseness is to use limited-information statistics. In this dissertation, two topics about constructing and using limited-information statistics to overcome sparseness for binary data will be included. In the first topic, the theoretical framework of pairwise concordance and the transformation matrix which is used to extract the corresponding marginals and their generalizations are provided. Then a series of new chi-square test statistics and corresponding orthogonal components are proposed, which are used to detect the model misspecification for longitudinal binary data. One of the important conclusions is, the test statistic $X^2_{2c}$ can be taken as an extension of $X^2_{[2]}$, the second-order marginals of traditional Pearson’s chi-square statistic. In the second topic, the research interest is to investigate the effect caused by different intercept patterns when using Lagrange multiplier (LM) test to find the source of misfit for two items in 2-PL IRT model. Several other directional chi-square test statistics are taken into comparison. The simulation results showed that the intercept pattern does affect the performance of goodness-of-fit test, especially the power to find the source of misfit if the source of misfit does exist. More specifically, the power is directly affected by the `intercept distance' between two misfit variables. Another discovery is, the LM test statistic has the best balance between the accurate Type I error rates and high empirical power, which indicates the LM test is a robust test.
ContributorsXu, Jinhui (Author) / Reiser, Mark (Thesis advisor) / Kao, Ming-Hung (Committee member) / Wilson, Jeffrey (Committee member) / Zheng, Yi (Committee member) / Edwards, Michael (Committee member) / Arizona State University (Publisher)
Created2022
Description
One common problem that occurs to students during breaks is the retrogression of knowledge due to lack of practice. This problem occurs for students at all levels of education but is especially harmful to students who are taking sequential classes such as Calculus for Engineers I and Calculus for Engineers II where the retention of topics taught in Calculus for Engineers I are required for students to succeed. One solution to this problem is the Keep in School Shape (KiSS) program. The KiSS program is a very efficient and easily accessible program that allows students to stay warmed up and ready to go when they start a sequential course by having daily review material during academic breaks.
During an academic break, students who are signed up for the KiSS program are sent a link through text message or email every day that allows them to access a multiple choice review problem. The review problem that they are given is a problem that presents material from the previous course that will be needed in the upcoming course. At the beginning of the review, students have the option to choose between a Level 1 or a Level 2 problem, where a Level 2 problem is related to its Level 1 counterpart but slightly more difficult. Before the students are permitted to solve the problem, they must first use a five point scale that indicates their confidence in their ability to solve the problem. After they complete either the Level 1 or Level 2 daily problem, those that got it wrong have the option to view a hint and try again or view a solution. The students that got the Level 1 daily problem right are also allowed to view the solution but will be permitted to go onto the next level right away whereas the students that got the Level 1 problem incorrect will need to try a similar problem before being able to move onto Level 2. For students who chose to do the Level 2 problem and were not very confident, they were given the option to solve a level 1 problem instead. Students who chose level 2 and got it wrong are given the options to view a hint and try again or simply view the solution before moving on to flashcard versions of the daily problems. Students who get the Level 2 problem correct are also given the option to continue practicing using the flashcards if they choose to.
Once a week, there is also a trivia day where students have the choice to complete solely a mathematical trivia question or complete both the trivia question along with a daily review problem. This feature allows students to take a day off from doing mathematics if they choose, but still stay engaged by doing a related activity.
Through this program, there is a lot to learn about whether doing Level 1 problems can help students improve their understanding of a concept enough to correctly solve a Level 2 problem. There are many factors to consider such as which question the student chose to answer first, student confidence, and student perseverance. Through the Summer Break 2023 KiSS program, there was data collected for every student answer for each day they accessed the daily KiSS activity. This thesis presents an analysis of the data showing how having two levels of problems is beneficial for students and the correlation between students’ results in Level 1 problems and Level 2 problems for students who chose to attempt both problems.
ContributorsWang, Ryan (Author) / Van de Sande, Carla (Thesis director) / Reiser, Mark (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor)
Created2023-12
Description
Tracking disease cases is an essential task in public health; however, tracking the number of cases of a disease may be difficult not every infection can be recorded by public health authorities. Notably, this may happen with whole country measles case reports, even such countries with robust registration systems. Eilertson et al. (2019) propose using a state-space model combined with maximum likelihood methods for estimating measles transmission. A Bayesian approach that uses particle Markov Chain Monte Carlo (pMCMC) is proposed to estimate the parameters of the non-linear state-space model developed in Eilertson et al. (2019) and similar previous studies. This dissertation illustrates the performance of this approach by calculating posterior estimates of the model parameters and predictions of the unobserved states in simulations and case studies. Also, Iteration Filtering (IF2) is used as a support method to verify the Bayesian estimation and to inform the selection of prior distributions. In the second half of the thesis, a birth-death process is proposed to model the unobserved population size of a disease vector. This model studies the effect of a disease vector population size on a second affected population. The second population follows a non-homogenous Poisson process when conditioned on the vector process with a transition rate given by a scaled version of the vector population. The observation model also measures a potential threshold event when the host species population size surpasses a certain level yielding a higher transmission rate. A maximum likelihood procedure is developed for this model, which combines particle filtering with the Minorize-Maximization (MM) algorithm and extends the work of Crawford et al. (2014).
ContributorsMartinez Rivera, Wilmer Osvaldo (Author) / Fricks, John (Thesis advisor) / Reiser, Mark (Committee member) / Zhou, Shuang (Committee member) / Cheng, Dan (Committee member) / Lan, Shiwei (Committee member) / Arizona State University (Publisher)
Created2022
Description
When most people think of Phoenix, Arizona, they think of sprawling cityscapesand hot desert mountains full of saguaros and other cacti. They rarely think of water and
fish, and yet, the Arizona landscape is home to many lakes, ponds, rivers and streams,
full of both native fish and sportfish, including in the urban areas. According to the report
by DeSemple in 2006, between the years 2001 and 2006, the Rio Salado Environmental
Restoration Project worked to revitalize the dry river bed that runs through Phoenix, that
included the construction of two urban ponds, the Demonstration Pond and the Reservoir
Pond. At the start of this study, it was unknown what vertebrate species inhabited these
ponds, but it was known that these urban ponds have been used to dump unwanted
aquatic pets. The bluegill Lepomis macrochirus was found to reside in both ponds, and as
it is such an important sportfish species, it was chosen as the focal species for these
studies, which took place over periods in March, May, July, and September of 2021.
Single-season occupancy models were used to attempt to determine how L. macrochirus,
use the microhabitats within the system, and a multi-season model was used to estimate
their recruitment, and seasonal changes in occupancy. In addition, this study also
attempts to understand the size structures of the L. macrochirus population in the
Reservoir Pond and the population in the Demonstration Pond, and if that size structure
varies from March to September. As the populations of these ponds are physically
isolated from one another, statistical tests were also done to determine if the size
structures of the two populations of L. macrochirus differ from one another and found
that the two populations do indeed differ from one another, but only during two of the
sampling periods.
ContributorsKeister, Emily Jan (Author) / Saul, Steven (Thesis advisor) / Bateman, Heather (Committee member) / Suzart de Albuquerque, Fabio (Committee member) / Arizona State University (Publisher)
Created2022