I test canonical theories in the preference literature - evolutionary psychology, social role theory, and social exchange theory - using group mean comparisons to replicate basic sex differences in spouse preferences. I find that, consistent with past studies, males prefer attractiveness and females prefer resources in potential partners, and in general, we prefer partners who are similar, rather than different, to us. I also find that males who anticipate enacting the "traditional" male role of "provider" within their marriage tend to prefer spouses who would fulfill the caregiver role, compared to males who do not anticipate such "traditional" gender divisions within the family. Interestingly, females who anticipate the "traditional" caregiving role do not in turn prefer spouses who fulfill the "provider" role; they instead prefer a spouse who is family-oriented, as they themselves are. I further test four new theoretical derivations and methodological assessment techniques. First, I expand the test of social exchange theory to include a wide array of personality characteristics and find similarity between how respondents see themselves and the types of characteristics they prefer in a spouse. Second, I include an assessment of gender endorsement - how respondents see themselves in terms of characteristics we commonly associate with masculinity and femininity. Interestingly, I don't find the predicted complimentarity - that highly masculine individuals prefer highly feminine spouses and vice versa. I find instead strong homogamy effects, such that respondents with masculine self-perceptions prefer spouses who also embody those masculine traits, and respondents with feminine self-perceptions prefer spouses who also identify with feminine traits. Third, my data includes a wider age range of unmarried respondents than nearly all other preference studies, so I am able to test preference differences by age. I find that older unmarried adults are generally less "particular" in their preferences, compared to those unmarried adults still in college. Despite my predictions that age would be positively related to the desire for spouse characteristics associated with "growing up," essentially, age appears to be negatively related or unrelated to most spouse preferences. Fourth, I include factor analysis techniques that both replicate a past research study (which was pioneering for the field), and broach the possibility for latent variable assessment using a wider array of preference dimensions than have been previously considered. I find evidence of several underlying preference constructs which could, and should, be taken into account when conducting future preference studies.

One of the most important decisions to make when performing an exploratory factor or principal component analysis regards the number of factors to retain. Parallel analysis is considered to be the best course of action in these circumstances as it consistently outperforms other factor extraction methods (Zwick & Velicer, 1986). Even so, parallel analysis could benefit from further research and refinement to improve its accuracy. Characteristics such as factor loadings, correlations between factors, and number of variables per factor all have been shown to adversely impact the effectiveness of parallel analysis as a means of identifying the number of factors (Pearson, Mundfrom, & Piccone, 2013). Critically, even the choice of criteria on which to evaluate factors (such as the eigenvalue at the 50th or 95th percentile) can have deleterious effects on the number of factors extracted (Peres-Neto, Jackson, & Somers, 2004). One area of parallel analysis yet to be researched is the magnitude of the difference between the actual eigenvalue and the random data-based eigenvalue. Currently, even if the margin between the actual eigenvalue and the random data-based eigenvalue is nominal, the factor is considered to be meaningful. As such, it may behoove researchers to enforce a higher standard, such as a greater margin between the two eigenvalues than just a simple difference. Accordingly, the purpose of this study was to evaluate the efficacy of a 10% margin criterion as compared to an absolute margin. These margins were evaluated in conjunction with the 50th, 90th, 95th, and 99th percentile eigenvalue criteria on a population correlation matrix designed to engender underextraction. Previous research (Matsumoto & Brown, 2017) explored the same conditions on a population correlation matrix designed to elicit overextraction. They found that the most stringent standard (99th percentile eigenvalue plus a 10% margin) was the most accurate. For the present study however, it was hypothesized that the most accurate results would be obtained from a standard less stringent than the 99th percentile eigenvalue plus a 10% margin. The results suggest that when a correlation matrix has properties which may illicit underextraction, the use of less stringent criteria may lead to greater accuracy in identifying the number of factors and that the incorporation of an additional margin criterion may not improve the accuracy of the analysis.

Safe drinking water is paramount to a healthy society. Close to a hundred contaminants are regulated by the government. Utilities are using chloramines to disinfect water to reduce harmful byproducts that may present themselves with the use of chlorine alone. Using chlorine and ammonia to disinfect, ammonia oxidizing bacteria can present themselves in an unsuspecting utilities distribution network. / Includes bibliography. / Thesis (M.S.)--Florida Atlantic University, 2019. / FAU Electronic Theses and Dissertations Collection

Student performance in college chemistry courses remains a concern for educators seeking to help improve the future STEM workforce. Besides math ability and prior chemistry knowledge, spatial ability and attitude toward chemistry have been considered as important factors influencing college chemistry performance. This work includes five studies and uses data collected from instruments to examine the relationships of these two factors - spatial ability and attitude - with student chemistry performance, and provides psychometric evidence for using the Purdue Visualization of Rotations test (ROT) and Attitude toward the Subject of Chemistry Inventory (ASCIv2) to measure these two factors, respectively, in college chemistry classrooms. The first two studies are about the evaluation and application of the ROT to measure the spatial ability of college chemistry students. Study 1, Sex difference in spatial ability for college students and exploration of measurement invariance, examines whether ROT items function in the same way between sexes. This study provides evidence that the ROT is an appropriate tool to measure the mental rotation component of spatial ability for college students. Results indicate the bi-factorial structure of ROT items, with each of the five items sharing the same rotation pattern. Thus, the item score is influenced by the general construct of mental rotation ability and the item rotation pattern. In addition, ROT items function in the same way across sexes; therefore, they can support the use of ROT for examining sex difference with less concern about test bias. A sex gap favoring males persists in the data. The second study, The role of spatial ability in students' progression through organic chemistry, examines whether students who scored low on the ROT in general chemistry are less likely to advance through organic chemistry, and the relationship of spatial ability to organic chemistry course grades for students who completed organic chemistry courses. The findings indicate that the ability to perform mental rotations, as measured by the ROT, does not present a barrier for students seeking to advance and succeed in the organic chemistry course sequence in the current setting after other factors, such as math ability, are held constant. For students who were at the low end of ROT, alternate approaches can be used to compensate for the lack of mental rotation ability to solve spatial-related chemistry problems, as suggested by the literature. The next three studies are about the evaluation and application of the ASCIv2 to measure student attitude toward chemistry. The ASCIv2 is based upon a previous publication, Refinement of a chemistry attitude measure for college students. Study 3, Attitude toward the subject of chemistry in Australia: An ALIUS and POGIL collaboration to promote cross-national comparisons, and Study 4, Gathering psychometric evidence for ASCIv2 to support cross-cultural attitudinal studies for college chemistry programs, gather psychometric evidence for the use of ASCIv2 internationally. The purpose for these two pilot studies is to investigate how ASCIv2 functions at multiple sites where the Process Oriented Guided Inquiry Learning (POGIL) is implemented with one of the objectives being to foster a positive attitude toward the subject in general. One student cohort is from a university in Australia, and the other is from a Saudi Arabian institution. The findings suggest ASCIv2 can be an appropriate tool to measure attitude in an Australian context; however, Saudi Arabian student cohorts responded differently to the item (chemistry is challenging vs. unchallenging), which raises concern about using these items to measure the attitude subscale for students in Saudi Arabia. As compared to Australian and Saudi Arabian students, US students at SE exhibited a negative attitude towards chemistry. Special attention should be paid to ways of getting students more interested in Chemistry. The last study, College students' attitudes toward chemistry, conceptual knowledge and achievement: structural equation model analysis, examines the contribution of attitude to chemistry performance when math ability and prior chemistry conceptual knowledge are controlled. Results reveal that a full SEM model using three predictors at the beginning of the semester can explain a very high percentage (69%) of the variance in chemistry achievement at the end of course. Both prior conceptual knowledge and attitude toward chemistry contribute a significant unique portion to the prediction of chemistry achievement when controlling for math ability. Therefore, we should not ignore the importance of student conceptual understanding and attitude. Additional analysis was performed using both ROT and ASCIv2. Results from multiple regression analysis indicate that the unique contribution of the ROT score to the ACS general chemistry exam score is not significant when other variables, such as attitude and math ability, are controlled.

"February 1992" Bibliography: leaf 323-344. Develops a general strategy for factorial linear model analysis for experimental and observational studies, an iterative, four-stage, model comparison procedure. The approach is applicable to studies characterized as being structure-balanced, multitiered and based on Tjur structures unless the structure involves variation factors when it must be a regular Tjur structure. It covers a wide range of experiments including multiple-error, change-over, two-phase, superimposed and unbalanced experiments.

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Thesis (Ph.D. (Marketing))--North-West University, Vaal Triangle Campus, 2004.

The purpose of this research was to explore the factorial validity of the National Survey of Student Engagement (NSSE), a survey widely used by institutions of higher education. Specifically, using data collected from first-year students and seniors at The University of Tennessee, Knoxville (UT), this research addressed three research questions. First, to what extent does the five-factor model of NSSE (i.e., the benchmark model) exhibit factorial validity? Second, to what extent is Pike’s (2006b) scalelet model of the NSSE factorially valid? Finally, is there a model that depicts the NSSE data better than the models consisting of benchmarks or scalelets? The participants of this study were first-year (n = 981) and senior (n = 944) students at UT who completed the online version of the NSSE in the spring of 2009. Using confirmatory factor analysis, results suggested poor model fit for both the benchmark model and Pike’s (2006b) scalelet model. Exploratory factor analysis with oblique rotation (Promax) resulted in a six-factor solution consisting of 27 items that accounted for approximately 39 percent of variance. The six-factor model failed, however, to exhibit sufficient model fit when confirmatory factor analysis was applied to a different data set (i.e., NSSE data collected in the spring of 2010). Overall, results suggest that much more validation research is needed for the National Survey of Student Engagement to ensure that its use among institutions of higher education is appropriate.

No description available.

Objectives<p>The geometric configuration of skull is complex and unique to each individual. The main objectives of this study are two fold: 1) to provide a new technique to define the outline of skull profile and 2) to find the common factors defining the ultimate skull configuration in adult population. The secondary objective was to explore the effect of age and sex on skull shape formation.<p>Materials & Methods <p>Ninety-three lateral skull x-ray from the CT scan films were selected and digitized. The lateral skull surface was divided into 3 regions based on the presumed location of coronal and lambdoid sutures. A software program (Canvas 7) was used to match the outer surface of lateral skull with circular curves. Three main curvatures (frontal, parietal, occipital) were consistently identified to overlap the skull periphery. The radius, cord length and inclination of each curvature were measured.. Factor analysis technique was also used to reduce the number of variables explaining the overall shape of skull. Student t-test and regression analysis was also used to explore the effect of sex and age on skull shape. <p>Results <p>There were total of 93 patients in this study (54% male). The average values for three defined curvatures of the skull profile were recorded. Factor analysis produced 3 factors. The first factor explained 32% of total variance and was related to the overall size of the head as represented by total length and the radius of the curvature in vertex and back of the head. The second factor covered 26% of the variance representing the inverse correlation between the angle of the frontal and parietal curves. The third factor revealed the direct correlation of occipital and parietal angle. In all of these factors, the frontal zone variation was independent or opposite of the parieto-occipital zone. A strong direct association between the total length of skull, occipital curve radius and length with the sex was shown. No age related variable was identified.<p>Conclusions <p>There is a large variation in the values of different part of the skull. The skull profile topography can be defined mathematically by two distinct territories: frontal and parieto-occipital zones. These territories hinge on the coronal suture. Therefore, coronal suture may play a dominant role in final skull configuration.