The Misspecification of Components and Factors

Factor and component analysis are two similar statistical procedures widely-used to reduce a set of p variables to a smaller set of m variables. This reduced set of m components or factors can be interpreted as an overall pattern structure or used in the derivation of factor and component scores. A commonly occurring and potentially serious problem concerns the misspecification of the number of factors and components (m). Misspecifications can take the form of extracting too many or too few factors or components. A series of simulation studies was undertaken to determine the practical effects of such misspecifications within and between the methods of maximum likelihood factor analysis (MLFA) and principal component analysis (PCA). Computer-simulated data sets, representing baseline factor and component patterns, were generated to represent a wide range of conditions. Item saturation, (aij - .4, .6 & .8), sample size (N - 75, 150, 225 & 450), and the variable to component and factor ratios (p:m - 4:1, 6:1 & 12:1) were systematically varied to create the baseline patterns prior to deliberate misspecifications. The problem was examined from several perspectives by investigating relationships within MLFA and PCA during both overextraction and underextraction, and by investigating relationships between MLFA and PCA during overextraction, underextraction and for the correct structural patterns. Results indicated an overall degradation in the MLFA and PCA solutions during both overextraction and underextraction. Although degradation within methods occurred during overextraction, little information was lost even at maximal overextraction for the strongest (aij = .8 & .6) pattern structures during either MLFA or PCA. By contrast, underextraction was a very serious problem with much loss of information occurring at the first underextraction and continuing with each successive underextraction. Greater degradation occurred with MLFA than PCA during underextraction. High similarity between MLFA and PCA solutions occurred for the correct pattern specifications and for the overextracted solutions. Low similarity between MLFA and PCA solutions occurred during underextraction. Item saturation was the major determinant, while sample size and variable to component (factor) ratio were lesser though important determinants, of stable pattern structures during overextraction and for correct solutions, both within and between methods. No condition of interest was found to be a consistent determiner of stable pattern structures during underextraction

The Relationship Antecedents of Smoking (RAS) Scale: A new scale to assess couple-focused triggers to smoke.

The purpose of this pilot study is to assess the reliability and construct validity of a measure of relationship-focused antecedents for smoking (RAS). The scale includes both positively-valenced items (e.g.. “I feel like smoking when I am relaxing with my partner”) and negatively-valenced items (e.g., “I feel like smoking when my partner criticizes me”). Participants included 123 individuals who smoke cigarettes with co-habitating smoking (n=63) or non-smoking (n=60) romantic partners. Participants completed the RAS and a series of measures associated with smoking outcomes. Principal component analysis with varimax rotation resulted in a 2-component solution. The RAS showed excellent internal consistency for the total scale (α=.96) and for the positive (α=.88) and negative (α=.97) subscales. Higher positive subscale scores were associated with lower motivation to quit while higher negative scores were associated with lower relationship satisfaction and dyadic efficacy to quit. Higher scores on both subscales were related to higher social motives, dependence motives, and social outcome expectances. Participants with smoking partners reported higher positive subscale scores and lower negative subscale scores. The RAS may be helpful in the design of smoking cessation interventions for couples

Internal Disinhibition Predicts Weight Regain Following Weight Loss and Weight Loss Maintenance

Objective: The disinhibition scale of the Eating Inventory predicts weight loss outcome; however, it may include multiple factors. The purpose of this study was to examine the factor structure of the disinhibition scale and determine how its factors independently relate to long-term weight loss outcomes. Research Methods and Procedures: Exploratory factor analysis of the disinhibition scale was conducted on 286 participants in a behavioral weight loss trial (TRIM), and confirmatory factor analysis was conducted on 3345 members of the National Weight Control Registry (NWCR), a registry of successful weight loss maintainers. Multivariate regressions were used to examine the relationships between the disinhibition scale factors and weight over time in both samples. Results: Using baseline data from TRIM, two factors were extracted from the disinhibition scale: 1) an internal factor that described eating in response to internal cues, such as feelings and thoughts; and 2) an external factor that described eating in response to external cues, such as social events. This factor structure was confirmed using confirmatory factor analysis in the NWCR. In TRIM, internal disinhibition significantly predicted weight loss at 6 months (p = 0.03) and marginally significantly predicted weight loss at 18 months (p = 0.06), with higher levels of internal disinhibition at baseline predicting less weight loss; external disinhibition did not predict weight loss at any time-point. In NWCR, internal disinhibition significantly predicted one-year weight change (p = 0.001), while external disinhibition did not. Discussion: These results suggest that it is the disinhibition of eating in response to internal cues that is associated with poorer long-term weight loss outcomes

Theory Testing Using Quantitative Predictions of Effect Size

Traditional Null Hypothesis Testing procedures are poorly adapted to theory testing. The methodology can mislead researchers in several ways, including: (a) a lack of power can result in an erroneous rejection of the theory; (b) the focus on directionality (ordinal tests) rather than more precise quantitative predictions limits the information gained; and (c) the misuse of probability values to indicate effect size. An alternative approach is proposed which involves employing the theory to generate explicit effect size predictions that are compared to the effect size estimates and related confidence intervals to test the theoretical predictions. This procedure is illustrated employing the Transtheoretical Model. Data from a sample (N = 3,967) of smokers from a large New England HMO system were used to test the model. There were a total of 15 predictions evaluated, each involving the relation between Stage of Change and one of the other 15 Transtheoretical Model variables. For each variable, omega‐squared and the related confidence interval were calculated and compared to the predicted effect sizes. Eleven of the 15 predictions were confirmed, providing support for the theoretical model. Quantitative predictions represent a much more direct, informative, and strong test of a theory than the traditional test of significance

Cancer prevention in primary care: Predictors of patient counseling across four risk behaviors over 24 months

Objective: Rates of preventive counseling remain below national guidelines. We explored physician and patient predictors of preventive counseling across multiple cancer risk behaviors in at-risk primary care patients. Methods: We surveyed 3557 patients, with at least one of four cancer risk behaviors: smoking, diet, sun exposure, and/or mammography screening, at baseline and 24 months. Patients reported receipt of 4A\u27s (Ask, Advise, Assist, Arrange follow-up); responses were weighted and combined to reflect more thorough counseling (Ask = 1, Advise = 2, Assist = 3, Arrange = 4, score range 0–10) for each target behavior. A series of linear-regression models, controlling for office clustering, examined patient, physician and other situational predictors at 24 months. Results: Risk behavior topics were brought up more often for mammography (90%) and smoking (79%) than diet (56%) and sun protection (30%). Assisting and Arranging follow-up were reported at low frequencies across all behaviors. More thorough counseling for all behaviors was associated with multiple visits and higher satisfaction with care. Prior counseling predicted further counseling on all behaviors except smoking, which was already at high levels. Other predictors varied by risk behavior. Conclusions: More thorough risk behavior counseling can be delivered opportunistically across multiple visits; doing so is associated with more satisfaction with care

Successful weight loss maintenance in relation to method of weight loss

This study examined the relation between method of weight loss and long-term maintenance among successful weight losers enrolled in a weight-loss maintenance trial. Participants were 186 adults (mean age = 51.6 +/- 10.7 years, mean BMI = 28.6 +/- 4.7 kg/m(2)) enrolled in the STOP Regain trial who had lost at least 10% of their body weight in the past 2 years using a very low-calorie diet (VLCD; n = 24), commercial program (n = 95), or self-guided approach (n = 67). Participants were randomized to a weight-maintenance intervention delivered face to face or over the internet or to a newsletter control condition, and followed for 18 months. At study entry, individuals who had used a VLCD had achieved a weight loss of 24% of their maximum weight within the past 2 years compared to 17% achieved by those who had used a commercial program or self-guided approach (P \u3c 0.001). However, individuals who had used a VLCD regained significantly more weight than the other two groups and by 6 months, there were no significant differences in overall percent weight loss (i.e., initial weight loss and maintenance) between VLCD, commercial, and self-guided methods. In contrast, individuals who had used a self-guided approach maintained their weight losses from baseline through 18 months. The large initial weight losses achieved by individuals who had used a VLCD were not maintained over time, whereas individuals who had used a self-guided approach maintained their initial weight losses with the greatest success. The generalizability of these findings is limited by the sizeable weight losses achieved by study participants

A Tribute to the Mind, Methodology and Mentoring of Wayne Velicer

Wayne Velicer is remembered for a mind where mathematical concepts and calculations intrigued him, behavioral science beckoned him, and people fascinated him. Born in Green Bay, Wisconsin on March 4, 1944, he was raised on a farm, although early influences extended far beyond that beginning. His Mathematics BS and Psychology minor at Wisconsin State University in Oshkosh, and his PhD in Quantitative Psychology from Purdue led him to a fruitful and far-reaching career. He was honored several times as a high-impact author, was a renowned scholar in quantitative and health psychology, and had more than 300 scholarly publications and 54,000+ citations of his work, advancing the arenas of quantitative methodology and behavioral health. In his methodological work, Velicer sought out ways to measure, synthesize, categorize, and assess people and constructs across behaviors and time, largely through principal components analysis, time series, and cluster analysis. Further, he and several colleagues developed a method called Testing Theory-based Quantitative Predictions, successfully applied to predicting outcomes and effect sizes in smoking cessation, diet behavior, and sun protection, with the potential for wider applications. With $60,000,000 in external funding, Velicer also helped engage a large cadre of students and other colleagues to study methodological models for a myriad of health behaviors in a widely applied Transtheoretical Model of Change. Unwittingly, he has engendered indelible memories and gratitude to all who crossed his path. Although Wayne Velicer left this world on October 15, 2017 after battling an aggressive cancer, he is still very present among us

On the reporting and review requirements of ISO 14044

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