PROC CALIS Research Articles

Associations of Appetitive Traits and Parental Feeding Style With Diet Quality During Early Childhood

BackgroundAppetitive traits and parent feeding styles are associated with body mass index in children, yet their associations with child diet quality are unclear. ObjectiveThe objective was to examine relations of appetitive traits and parental feeding style with diet quality in 3.5-year-old children. DesignThe study was a secondary, cross-sectional analysis of data from Sprouts, a follow-up study of the Pregnancy Eating Attributes Study (PEAS). Birthing parents completed the Child Eating Behavior Questionnaire, Caregiver’s Feeding Styles Questionnaire, and proxy 24-hour dietary recalls for their children from February 2019 to December 2020. Participants/settingParticipants were 162 birthing parents (early pregnancy BMI ≥ 18.5 and absence of preexisting diabetes, any medical condition contraindicating study participation, self-reported eating disorder, or medications that could affect diet or weight) and their children living in North Carolina. Main outcome measuresHealthy Eating Index—2015 (HEI-2015) total scores were calculated. Statistical analyses performedPath modeling was conducted using PROC CALIS with full information maximum likelihood (FIML) to account for missing data (< 2% of all data in dataset). Associations of child appetitive traits and parental feeding style with child HEI-2015 scores, adjusting for exclusive breastfeeding duration and household income–poverty ratio, were examined. Tests of simple effects were conducted in subsamples split by parental feeding style. Hypotheses were formulated during data collection. ResultsA 1-standard deviation (SD) greater food fussiness was associated with a 2.4-point lower HEI-2015 total score (P = .02; 95% confidence interval [CI] [–4.32, –0.48]) in children. When parental feeding style was authoritarian, a 1-SD greater food responsiveness was associated with a 4.1-point higher HEI-2015 total score (P = .007; 95% CI [1.12, 7.01]) in children. When parental feeding style was authoritative, a 1-SD greater slowness in eating was associated with a 5.8-point lower HEI-2015 total score (P = .01; 95% CI [–10.26, –1.33]) in children. ConclusionsParental feeding style may modify the association of appetitive traits with diet quality in young children. Future research could determine whether matching parent feeding styles to child appetitive trait profiles improves child diet quality.

Gender differences in the mediational pathway between trauma, depression and subjective cognitive decline

AbstractBackgroundAdverse childhood experiences (ACEs) have been linked to subjective cognitive decline (SCD) in later life, which may be a precursor for Alzheimer’s disease. However, studies examining the potential mechanisms between ACEs and SCD as well as the differential role that gender might play in these pathways are lacking. The aim of this study was to assess how gender influences the association between ACEs, depression and SCD.MethodData were obtained from 14,630 respondents (6,254 men and 8,376 women) from the 2021 US Behavioral Risk Factor Surveillance System survey. Trauma was operationalized as the experience of ACEs. A depression categorization was based on respondents’ self‐report of ever being informed of having a depressive disorder. SCD was operationalized as respondents reporting having experienced increasing confusion or memory loss in the past 12 months. Crude and adjusted stratified path analyses using PROC CALIS were conducted to determine the direct and indirect associations between ACEs, depression, and SCD overall and by gender.ResultPreliminary analyses show that in the overall study population, respondents who reported experiencing ACEs were more likely to report depression (B = 0.165; p&lt;0.0001) and those who reported a depression diagnosis were more likely to report SCD (B = 0.191; p&lt;0.0001) in the past year. There was also a direct positive association between ACEs and SCD (B = 0.085, p&lt;0.0001) where respondents with a history of ACEs were more likely to report SCD. Depression mediated the association between ACEs and SCD (B = 0.032; p&lt;0.0001) Stratified path analyses showed similar findings for men and women where depression was a mediator in the relationship between ACEs and SCD (men: B = 0.025; p&lt;0.0001; and women: B = 0.036; p&lt;0.0001).ConclusionDepression mediated the association between ACEs and SCD in the overall population, and among men and women. There was no moderating role of gender in the mediational pathway between ACEs, depression and SCD. Further analyses will be conducted to elucidate the interaction effects in these data. Future studies should assess the moderating role of gender in alternative mediational pathways such as examining substance use, and PTSD as potential mediators in the relationship between ACEs and SCD.

Combined Logistic and Confined Exponential Growth Models: Estimation Using SEM Software

The logistic and confined exponential curves are frequently used in studies of growth and learning. These models, which are nonlinear in their parameters, can be estimated using structural equation modeling software. This paper proposes a single combined model, a weighted combination of both models. Mplus, Proc Calis, and lavaan code for the model are provided. Monte Carlo simulations varying the number of measurement occasions (5, 10, and 15), internal consistency (α = 0.5, 0.7, and 0.8), and sample size (N = 1,000, 500, and 300) were examined to understand whether the model can be successfully fit with SEM software. Convergence failures were appreciable when model parameters were equal to special cases of logistic or confined exponential curves. At least ten measurement occasions and a moderate degree of reliability (α > 0.7) were required to identify the model as superior to its stand-alone alternatives.

What makes electricity consumers change their behavior? Influence of attitude and perceived impact of DR programs on awareness

PurposeIn this study, the authors propose a confirmatory factor analysis (CFA) to create a tenable measurement model and identify the factors that have the potential to enhance awareness of pro-environmental measures. The successful implementation of demand response (DR) programs and their required infrastructure is significant for moving towards green energy communities and a better environment for living. Not only can renewable energy capacities contribute to this desideratum, but also electricity consumers who, until the last decade, have played a passive role.Design/methodology/approachTo answer these questions, a complex data set of 243 post-trial questions created by the Irish CER are analyzed using first-order and hierarchical CFA models with several SAS procedures (PROC CALIS, MIANALYZE). The questionnaire was launched to over 3,000 electricity consumers from Ireland that were participants to a trial program after the installation of smart metering systems and implementation of DR programs.FindingsThe effect of five latent factors – positive attitude, negative attitude, perceived impact of own actions, price- and incentive-DR programs – is measured. With a bi-factor CFA measurement model, the authors assess that they significantly influence the electricity consumers' awareness.Research limitations/implicationsHowever, these findings have to be backed up by relevant information and simulations showing consumers benefits in exchange to their efforts. They have research implications on the design of the business models and DR programs pointing out the importance of benefits and fairness of value sharing mechanisms within energy communities.Practical implicationsThus, the electricity consumers may change their consumption behavior as they positively perceive the implementation of DR programs.Originality/valueThis paper fulfills an identified need to study post-trial questionnaire and reveal latent factors that make electricity consumer change their behavior.

Analysing observed categorical data in SPSS AMOS: a Bayesian approach

This study has a didactic purpose to help applied investigators and practitioners to understand the roles of observed categorical data (OCD) in structural equation modelling (SEM) and the appropriate ways of analysing such data under SPSS AMOS. To that end, the study reviews types of OCD (nominal, ordinal, dichotomous and polytomous) and their incorporation into SEM under AMOS to play different roles. The study presents two applications from the health and retirement study where Bayesian statistical inference is used to analyse one set of OCD variables serving as endogenous variables with/without groups created by another OCD variable. Besides, the study demonstrates the typical ways of summarising, reporting and interpreting the results from Bayesian statistics, and compares AMOS with several other SEM programmes (Mplus, R lavaan, Stata and SAS PROC CALIS) on handling OCD. The study concludes with summaries of the findings for its intended audience.

Unboxing the Black Box: Demystifying the Impact of Consumers’ Psychological Motivations on Their Perception of Online Advertising

In a quest to reap the potential of the internet as an advertising media, marketers are increasing the share of online advertising in their promotion mix. But very less is known about factors impacting the consumers’ perception of online advertising. Psychological factors play an important role in developing the consumers perception, the present study extends the concept in the domain of online advertising. For this, the present study has developed a hypothesized model containing two layers. Layer one consists of a conceptual framework based on the literature review and second layer comprised of testing the relationships between consumers psychological motivations and their perception of online advertising. For the purpose, information, convenience, entertainment and social interaction are considered as psychological motivations of using the internet. The consumers’ perception of online advertising has been measured in terms of information value, entertainment value, trustworthiness, offensiveness and incentives. A purposive survey was conducted in Delhi NCR and the data was analysed using SEM in SAS Proc Calis (9). The findings suggest that psychological motivations of using the internet significantly impact the consumers’ perception of online advertising.

Reactance and turbulence: examining the cognitive and affective antecedents of ad blocking

PurposeOne of the most effective tools used by interactive marketers is personalized advertising, which allows consumers to directly respond to customized offers to purchase a brand’s products and services. Yet, recent studies show many consumers are installing ad blockers to avoid personalized ads. This study aims to examine how ad skepticism, ad relevance and ad irritation predict ad avoidance directly, as well as indirectly through consumers’ attitudes toward personalized advertising. Also, considered were how these antecedents’ study in tandem to trigger consumers’ desire to avoid ads by installing ad-blocking software.Design/methodology/approachAn online survey was administered to a pool of 1,313 paid panelists who were familiar with ad blocking and reported that they either currently used an ad blocker, previously used an ad blocker, were considering using an ad blocker or did neither use nor were they considering using an ad blocker. All hypotheses were addressed via path modeling using PROC CALIS in SAS 9.4.FindingsResults indicate that attitudes toward personalized advertising are more complex than attitudes toward advertising in general and mediate the effect of ad relevance on ad avoidance. Likewise, trust in interactive marketers moderates attitude toward personalized advertising and the negative outcomes of ad avoidance and ad blocker usage among skeptical consumers. Also, the reported differences in ad avoidance based on participants’ current vs previous ad blocker usage suggest that former users are using a more sophisticated evaluation of the costs and benefits of using ad blockers.Practical implicationsConsumers’ trust in an interactive marketer to properly collect and use their information plays an important role in moderating negative outcomes associated with personalized advertising. Also, the key is the use of high-quality data (best obtained through a permission-based relationship with the consumer) to deliver relevant ads without stimulating reactance or (privacy-related) boundary turbulence. Findings suggest that bolstering trust by engaging in a transparent, permission-based relationship with consumers may mitigate the tendency to adopt ad blockers and enhance the effectiveness of interactive marketing efforts.Originality/valueAd blocking presents a significant threat to the effectiveness of interactive marketing efforts like personalized advertising. Previous research on the antecedents of ad blocking is limited, considers a broad range of factors and offers mixed findings. The present study examines an informed set of cognitive and affective factors suggested by previous ad blocking studies to predict consumers’ desire to avoid personalized ads by installing ad-blocking software. Given the continued threat to the interactive marketing industry posed by ad blocking, a greater understanding of consumers’ motivations to adopt and use ad blockers is critical.

Causal relationships from legume crops to soil microbial properties relative to canola

AbstractLegume crop rotational effects are usually studied in only the first subsequent non‐legume crop even though several consecutive crops usually follow a legume. We studied the effects of field pea (Pisum sativum L.), faba bean (Vicia faba L.), faba bean green manure (faba GM), lentil (Lens culinaris Medik.), canola (Brassica napus L.), and wheat (Triticum aestivum L.), on soil microbial biomass carbon (MBC), β‐glucosidase enzyme activity, and bacterial physiological diversity in three subsequent crops at four locations. Generalized linear modeling (SAS PROC GLIMMIX) indicated that, when canola is grown 3 yr after an initial canola crop in the rotation, MBC is 4–40% (Bonferroni‐adjusted limits at 95% confidence) greater than when faba bean is the initial crop. Path modeling (SAS PROC CALIS) confirmed the negative effect on MBC by faba bean (relative to canola) as an initial crop. According to Bonferroni‐adjusted limits at 95% confidence, where faba GM was the initial crop, β‐glucosidase activity was 2–24% greater than where faba bean was the initial crop and 0.4–21.8% greater than where wheat was the initial crop. Similarly, where lentil was the initial crop, β‐glucosidase activity was 2–23% greater than where pea was the initial crop and 3–5% greater than where wheat was the initial crop. Path modeling revealed direct causal relationships from faba GM and lentil to β‐glucosidase activity. The legume crop effects on soil microbial properties were: faba GM &gt; lentil &gt; pea &gt; faba bean, but we did not observe diminishing effects of the initial legumes to consecutive subsequent crops.

Genetic alteration preceding any chronic diseases: using Human Genomic Project

Abstract: Since the human genomic project had been completed in 2003, scarce research studies have been done to evaluate the clinical relevance of this project to public health, specifically in the arena of prevention of chronic diseases. Utilizing the structural equation model, with a random sample from National Lung Screening Data. Using SAS software and Proc CALIS for the analysis to assess whether there is a genetic alteration/expression transpires prior to any chronic disease. And to encourage more research studies in this rookie field that merges both public health and prevention of chronic diseases with the human genome. The results of all three proposed models boost the alternative theory, which indicates there is gene alteration/expression anterior to any chronic disease. Therefore, the results stimulate the use of the human genome project in the area of public health in a way that can curtail many dangerous chronic diseases before they hit.

Longitudinal associations between smoking and affect among cancer patients using varenicline to quit smoking

During a quit attempt, high negative affect predicts relapse to smoking. In this study, we evaluated bidirectional longitudinal associations between smoking and negative affect among cancer patients treated with varenicline. Participants (N = 119, 50% female, Mage = 59 years) were smokers (≥5 cigarettes/week) who were diagnosed with cancer and were recruited for a 24-week trial of extended duration varenicline plus behavioral counseling; data for this secondary analyses were drawn from the 12-week open-label phase of the trial. Smoking was assessed via self-reported number of cigarettes in the past 24 h. Negative affect was assessed using the Positive and Negative Affect Scale (PANAS). Data were collected at pre-quit (week 0), target quit day (week 1), week 4, and week 12. We evaluated cross-lagged panel models for negative affect and smoking using PROC CALIS in SAS. Models were run separately for participants who were adherent (≥80% of medication taken) or nonadherent to varenicline. Among adherent participants (n = 96), smoking accounted for up to 22% of variance in subsequent negative affect throughout treatment. Cross-lagged associations were not observed between smoking and negative affect among non-adherent participants (n = 23). Negative affect did not predict subsequent smoking among either adherent or nonadherent participants. These results suggest that varenicline may attenuate abstinence-induced negative affect among cancer patients treated for nicotine dependence.

Implementing a Simulation Study Using Multiple Software Packages for Structural Equation Modeling

A Monte Carlo simulation study is an essential tool for evaluating the behavior of various quantitative methods including structural equation modeling (SEM) under various conditions. Typically, a large number of replications are recommended for a Monte Carlo simulation study, and therefore automating a Monte Carlo simulation study is important to get the desired number of replications for a simulation study. This article is intended to provide concrete examples for automating a Monte Carlo simulation study using some standard software packages for SEM: Mplus, LISREL, SAS PROC CALIS, and R package lavaan. Also, the equivalence between the multilevel SEM and hierarchical linear modeling (HLM) is discussed, and relevant examples are provided. It is hoped that the codes in this article can provide some building blocks for researchers to write their own code to automate simulation procedures.

Structural Equation Modeling in a Near-Highway Exposure Study: Ultrafine Particles and Association with Cardiovascular Disease Risk

Background: Structural equation modeling (SEM) is a statistical method that has not been used widely in epidemiological studies of ambient air pollution. Aims: Assess the association between individually-calculated exposure to UFP (&lt;100 nm, estimated as particle number concentration or PNC) and cardiovascular disease risk. Methods: Air pollution data based on 55 days of mobile monitoring was used to build a regression model for assigning residential ambient hourly PNC for participants of the Community Assessment of Freeway Exposure and Health (CAFEH) study (N=140, a subset of CAFEH). Participants completed questionnaires on residential and occupational exposure, income, education, smoking, diet, physical activity and stress. Blood samples were analyzed for C-reactive protein (CRP), interleukin-6 (IL-6), tumor necrosis factor-? receptor II (TNF?); fibrinogen. Ankle brachial pressure index (ABI) as well as systolic, diastolic and pulse pressures were also measured. SEM was conducted using Proc Calis in SAS to determine path loadings, p-values between latent variables, and the individual variables contributing to the latent variables. Results: CRP, IL-6 and TNF? were not normally distributed and had population median values of 1.62mg/L for CRP; 1.61pg/mL for IL-6; and 2256pg/mL for TNF?. Fibrinogen was normally distributed with a mean of 475mg/dL. Initial SEM model development for the dependent latent variable construct cardiovascular disease risk produced the largest standardized estimates with the indicator variables CRP, TNF?, BMI, hypertension, and IL-6. PNC and the independent latent variable construct other combustion exposures displayed a positive association with cardiovascular disease risk, while and socio-economic status displayed a negative association. Conclusion: Initial analysis indicates that our model may have one endogenous latent variable, cardiovascular disease risk, and two or more exogenous latent variables related to air pollution and lifestyle.

Recent Developments in Structural Equation Modelling Research in Social Work Journals

The use of various structural equation modelling methods in social work research continues to expand. As more social work researchers become acquainted with structural equation modelling (SEM), there has been an increase in the application of the methods in social work academic journals. The study reported here is a systematic review of the literature covering SEM studies in social work journals that were published between February 2007 and March 2012. Among the factors associated with the increased use of SEM in social work research are the availability of user-friendly statistical software, such as LISREL, AMOS and EQS, as well as additional software including Mplus, SAS (Proc Calis), Mx and R (lavaan.org). Based on the 2010 Journal Citation Reports, the review found that, indeed, there is improvement in both the number and quality of SEM studies. Specifically, n = 59 studies were published in seventeen social work journals within the specified time frame. Discussion is directed towards improving SEM application in social work research.

A Review of Eight Software Packages for Structural Equation Modeling

This article reviews eight different software packages for linear structural equation modeling. The eight packages—Amos, SAS PROC CALIS, R packages sem, lavaan, OpenMx, LISREL, EQS, and Mplus—can help users estimate parameters for a model where the structure is well specified. Capabilities for handling single group, multiple group, nonnormal variables, and missing data are considered and the eight packages are compared across a variety of criteria from documentation to parameter estimation. The main difference between the packages is the presence of a graphical interface for model specification and presentation of results. Each package differs in terms of strengths, areas of improvement, and unique features that may dictate the choice of selection. Some suggestions on areas of improvement for all software packages are made. This article has supplementary materials online.

병원간호사의 의료관련감염 예방을 위한 손위생에 관한 구조모형

Purpose: The purpose of this study was to test hand hygiene behavior model of hospital nurses, based on theory of planned behavior. Methods: Data were collected from 253 nurses from four university hospitals for the period of December 2010 to January 2011. Data were analyzed using of SAS (ver.9.1). Fitness of the study model was identified with SAS PROC CALIS. Results: The overall fitness was <TEX>$x^2$</TEX>=57.81 (df=13, <TEX>$p$</TEX> <.001), GFI=.99, AGFI=.99, CFI=.95, NFI=.93. The variance of actual implementation of hand hygiene by predictor variables was 11.0% and the variance of intention to hand hygiene was 53.5%. Variable that had a direct effect on hand hygiene behavior was intention. Perceived behavior control and attitude affected hand hygiene behavior indirectly. Control belief had a direct effect on perceived behavior control and had an indirect effect on intention and behavior. Behavioral belief had a direct effect on attitude and an indirect effect on intention and behavior. Conclusion: The study provides basic information for understanding nurses' hand hygiene behavior. Further testing of the model will indicate which variables can contribute to improved hand hygiene.

A Pathway-based Analysis of Urinary Arsenic Metabolites and Skin Lesions

Inorganic arsenic is metabolized to monomethylarsonic acid (MMA) and dimethylarsinic acid (DMA). Limited evidence suggests that the ability to fully metabolize arsenic into DMA influences susceptibility to disease. To determine whether percentage of MMA was predictive of disease, the authors used data from a case-control study conducted in Bangladesh (2001-2003). Persons who were diagnosed with keratosis, melanosis, Bowen's disease, or squamous cell carcinoma were matched on age, sex, and village to persons without these conditions. This analysis was restricted to persons who had no missing data on covariates (859 cases, 868 controls). A path analysis was used to evaluate simultaneously the association between the percentage of all urinary arsenic metabolites and the odds of skin lesions using PROC CALIS in SAS, version 9.1 (SAS Institute, Inc., Cary, North Carolina) and Mplus, version 6.1 (Muthén & Muthén, Los Angeles, California). The odds of skin lesions were significantly associated with log(10) percentage of MMA (adjusted odds ratio (OR(adj)) = 1.56, 95% confidence interval (CI): 1.15, 2.12) but not log(10) percentage of inorganic arsenic (OR(adj) = 1.06, 95% CI: 0.75, 1.50) or log(10) percentage of DMA (OR(adj) = 1.07, 95% CI: 0.33, 3.46). This novel analysis confirmed that persons who excrete a higher proportion of MMA have a greater risk of skin lesions after data are adequately controlled for urinary arsenic metabolites, current arsenic exposure, and other risk factors.

The Dose-response Relationship Between Urinary Arsenic Metabolites and Skin Lesions Using a Pathway Approach

S-29B7-2 Background/Aims: Inorganic arsenic (As) is metabolized to monomethylarsonic acid (MMA) and dimethylarsinic acid (DMA). Limited evidence suggests that an individual's ability to fully metabolize MMA to DMA influences susceptibility to As-induced health effects including cancer. A case-control study conducted in Bangladesh (2001–2003) was used to evaluate the association between metabolism and skin lesions, an early symptom of As toxicity. Methods: A subset of individuals diagnosed with keratosis, melanosis, Bowen disease, or squamous cell carcinoma (n = 881) and individuals without these conditions (n = 868) were used in this analysis. The percentage of each urinary As metabolite was log10 transformed and used as a biomarker of methylation capacity. A novel pathway analysis was used to simultaneously evaluate the association between all urinary arsenic metabolites and the odds of skin lesions using PROC CALIS and Mplus. Additional covariates, including drinking water arsenic, age, creatinine, sex, education, chewing betel nut, and body mass index were also included as covariates. Results: The path analysis explained 44%, 13%, and 8% of the variance in %DMA, %MMA, and %iAs, respectively. We found that the odds of skin lesions was significantly associated with log10%MMA (ORadj: 1.62; 95% confidence interval [CI]: 1.07, 2.47) but not log10%iAs (ORadj: 1.20, 95% CI: 0.78, 1.84) nor log10%DMA (ORadj: 1.46, 95% CI: 0.36, 5.89). Conclusion: This analysis confirmed that individuals who excrete higher levels of MMA have a greater risk of skin lesions while adequately controlling for current arsenic exposure, all urinary arsenic metabolites, and other risk factors.

The Influence of Travel Experience on Mature Travelers’ Quality of Life

The purpose of this study was to examine the influence of past travel experience (i.e., number of trips and number of days away from home in last year), and on mature travelers’ quality of life (i.e., self-perceived health and global life satisfaction). A total number of 217 respondents (50+) in a southern state were used in this study. Path analysis (PROC CALIS in SAS) was performed to test the proposed model. An estimation of the proposed theoretical model revealed that the model fit the data. However, the model should be further examined and applied with caution.

Software Development Process on Proc Calis

The paper aimed to construct a GUI platform for PROC CALIS by developing scripts integrating a GUI program with SAS Base. PROC CALIS, a module estimating models via Structural Equation Modeling (SEM), is a procedure in SAS Base. As SAS Base is still very much script based, the research attempts to alleviate the script based module to a GUI module. Rapid Application Development (RAD) methodology was deployed to allow a structured, robust and faster prototyping application development. Findings revealed that the prototype was successful integrating the GUI module with SAS Base. The results output panel was also improved to allow a less cluttered display of results.

A Note on Multigroup Comparisons Using SAS PROC CALIS

Although SAS PROC CALIS is not designed to perform multigroup comparisons, it is believed that SAS can be “tricked” into doing so for groups of equal size. At present, there are no comprehensive examples of the steps involved in performing a multigroup comparison in SAS. The purpose of this article is to illustrate these steps. We demonstrate procedures using an example to evaluate the measurement invariance of communication satisfaction and organizational justice across 2 groups. Following the approach outlined in Byrne (2004), we conduct the same analysis in AMOS and compare the results to those obtained in SAS. We show that the sample size must be input correctly and the degrees of freedom must be adjusted in order for the standard errors and goodness-of-fit statistics to be correct. In addition, several of the fit indexes must be modified to obtain the correct values.