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PubMed2005

An analysis of dimensionality using factor analysis (true-score theory) and Rasch measurement: what is the difference? Which method is better?

One often hears the question asked, "For questionnaire data measuring a variable, what difference does it make to use factor analysis/principal components analysis (true-score theory) or Rasch measurement in testing for dimensionality?" This paper reports both factor analysis and Rasch measurement analysis for two sets of data. One set of data measures social anxiety for primary school students (N=436, I=10) and the second measures attitude to mathematics for primary-aged students (N=774, I=10). For both sets of data, the factor analysis suggests that the scores are reliable, and that inferences can be made that are valid for measuring school anxiety and attitude to mathematics. For both sets of data analyzed with Rasch measurement techniques, the reliability of the measures, the dimensionality of the measures, and the initial conceptualisation of the items, are called into question. It suggests that one cannot make valid inferences from the measures that were initially set up for true-score theory. The Rasch analysis suggests that items intended to measure a variable should be initially developed on a conceptualized scale from easy to hard, and that students should answer the items from this perspective, so that the Rasch analysis of the data tests this conceptualisation, and a linear scale can be created based on a mathematical measurement model with consistent units (logits).

Anxiety Disorders↗
PubMed2005

Factor analysis of lifestyle-related factors in 12,525 urban Japanese subjects.

This study describes the clustering patterns of several lifestyle-related factors in urban Japanese subjects. The effect of aging on these patterns was also investigated. Data of 8 factors that included body mass index (BMI), blood pressure (BP), fasting plasma glucose (FPG), serum total cholesterol (TC), triglycerides (TG), high-density lipoprotein cholesterol (HDLc), gamma-glutamyl-transferase (GGT), and cigarette smoking were analyzed for 12,525 individuals (4,591 men and 7,934 women) aged either 40, 50, or 60 years. Factor analysis showed eight factors clustered into 3 unrelated groups. BMI and BP were excluded in subjects aged 60 years. Our data showed that the effect of obesity on the prevalence of type 2 diabetes mellitus was age dependent. In spite of the established inverse relationship between TG and HDLc, we found that TG had an association with GGT. These results indicated that aging may have a major influence on the expression of multiple risk factors. The influence of BMI on the lifestyle-related factors appeared to be mostly expressed in younger people, while these factors appeared to be independent of BMI at age 60.

Adult↗
PubMed2006

A single factor underlies the metabolic syndrome: a confirmatory factor analysis.

OBJECTIVE: Confirmatory factor analysis (CFA) was used to test the hypothesis that the components of the metabolic syndrome are manifestations of a single common factor. RESEARCH DESIGN AND METHODS: Three different datasets were used to test and validate the model. The Spanish and Mauritian studies included 207 men and 203 women and 1,411 men and 1,650 women, respectively. A third analytical dataset including 847 men was obtained from a previously published CFA of a U.S. population. The one-factor model included the metabolic syndrome core components (central obesity, insulin resistance, blood pressure, and lipid measurements). We also tested an expanded one-factor model that included uric acid and leptin levels. Finally, we used CFA to compare the goodness of fit of one-factor models with the fit of two previously published four-factor models. RESULTS: The simplest one-factor model showed the best goodness-of-fit indexes (comparative fit index 1, root mean-square error of approximation 0.00). Comparisons of one-factor with four-factor models in the three datasets favored the one-factor model structure. The selection of variables to represent the different metabolic syndrome components and model specification explained why previous exploratory and confirmatory factor analysis, respectively, failed to identify a single factor for the metabolic syndrome. CONCLUSIONS: These analyses support the current clinical definition of the metabolic syndrome, as well as the existence of a single factor that links all of the core components.

Blood Pressure↗
PubMed2005

Are factor analytical techniques used appropriately in the validation of health status questionnaires? A systematic review on the quality of factor analysis of the SF-36.

Factor analysis is widely used to evaluate whether questionnaire items can be grouped into clusters representing different dimensions of the construct under study. This review focuses on the appropriate use of factor analysis. The Medical Outcomes Study Short Form-36 (SF-36) is used as an example. Articles were systematically searched and assessed according to a number of criteria for appropriate use and reporting. Twenty-eight studies were identified: exploratory factor analysis was performed in 22 studies, confirmatory factor analysis was performed in five studies and in one study both were performed. Substantial shortcomings were found in the reporting and justification of the methods applied. In 15 of the 23 studies in which exploratory factor analysis was performed, confirmatory factor analysis would have been more appropriate. Cross-validation was rarely performed. Presentation of the results and conclusions was often incomplete. Some of our results are specific for the SF-36, but the finding that both the application and the reporting of factor analysis leaves much room for improvement probably applies to other health status questionnaires as well. Optimal reporting and justification of methods is crucial for correct interpretation of the results and verification of the conclusions. Our list of criteria may be useful for journal editors, reviewers and researchers who have to assess publications in which factor analysis is applied.

Factor Analysis, Statistical↗
PubMed2006

FACTOR: a computer program to fit the exploratory factor analysis model.

Exploratory factor analysis (EFA) is one of the most widely used statistical procedures in psychological research. It is a classic technique, but statistical research into EFA is still quite active, and various new developments and methods have been presented in recent years. The authors of the most popular statistical packages, however, do not seem very interested in incorporating these new advances. We present the program FACTOR, which was designed as a general, user-friendly program for computing EFA. It implements traditional procedures and indices and incorporates the benefits of some more recent developments. Two of the traditional procedures implemented are polychoric correlations and parallel analysis, the latter of which is considered to be one of the best methods for determining the number of factors or components to be retained. Good examples of the most recent developments implemented in our program are (1) minimum rank factor analysis, which is the only factor method that allows one to compute the proportion of variance explained by each factor, and (2) the simplimax rotation method, which has proved to be the most powerful rotation method available. Of these methods, only polychoric correlations are available in some commercial programs. A copy of the software, a demo, and a short manual can be obtained free of charge from the first author.

Behavioral Research↗
PubMed2001

Leptin and other components of the Metabolic Syndrome in Mauritius--a factor analysis.

OBJECTIVE: To use factor analysis to examine the putative role of leptin in the Metabolic Syndrome, and to define better the associations among observed variables and the identified factors. DESIGN: Factor analysis of cross-sectional data from a 1987 survey. SUBJECTS: Non-diabetic residents of Mauritius who participated in population-based surveys in 1987 and 1992 (1414 men and 1654 women). MEASUREMENTS: Fasting and 2 h plasma glucose and insulin following a 75 g oral glucose load; seated blood pressure; body mass index (BMI); waist-to-hip ratio (WHR); and fasting serum triglycerides, HDL-cholesterol, leptin and uric acid concentrations. RESULTS: Principal components factor analysis revealed three factors for men and women that explained between 54 and 55% of the observed variance of the 12 measured variables. General features of these factors were as follows: factor 1, WHR, BMI, leptin, fasting and 2 h insulin, triglycerides, and HDL-cholesterol; factor 2, systolic and diastolic blood pressure, uric acid (men only), and fasting glucose (women only); and factor 3, fasting and 2 h glucose and insulin. Only three variables loaded on more than one factor with a loading > or = 0.4 (fasting and 2 h insulin, fasting glucose in women only). Leptin loaded on one factor only in both men and women. CONCLUSIONS: Since multiple factors underlie the Metabolic Syndrome, and since no observed variable loads on all three factors, more than one mechanism might account for the observed clustering of risk characteristics. Leptin does not unite features of this syndrome due to its loading on one factor only. Uric acid is related to a different factor in men and women. The absence of gender differences in factor loadings argues for similar mechanisms for the Metabolic Syndrome in men and women in Mauritius. International Journal of Obesity (2001) 25, 126-131

Adult↗
PubMed2001

Quantification of regional myocardial blood flow using dynamic H2(15)O PET and factor analysis.

UNLABELLED: Because the use of factor analysis has been proposed for extracting pure physiologic temporal or spatial information from dynamic nuclear medicine images, factor analysis should be capable of robustly estimating regional myocardial blood flow (rMBF) using H2(15)O PET without additional C15O PET, which is a cumbersome procedure for patients. Therefore, we measured rMBF using time-activity curves (TACs) obtained from factor analysis of dynamic myocardial H2(15)O PET images without the aid of C15O PET. METHODS: H2(15)O PET of six healthy dogs at rest and during stress was performed simultaneously with microsphere studies using 85Sr, 46Sc, and 113SN: We performed factor analysis in two steps after reorienting and masking the images to include only the cardiac region. The first step discriminated each factor in the spatial distribution and acquired the input functions, and the second step extracted regional-tissue TACS: Image-derived input functions obtained by factor analysis were compared with those obtained by the sampling method. rMBF calculated using a compartmental model with tissue TACs from the second step of the factor analysis was compared with rMBF measured by microsphere studies. RESULTS: Factor analysis was successful for all the dynamic H2(15)O PET images. The input functions obtained by factor analysis were nearly equal to those obtained by arterial blood sampling, except for the expected delay. The correlation between rMBF obtained by factor analysis and rMBF obtained by microsphere studies was good (r = 0.95). The correlation between rMBF obtained by the region-of-interest method and rMBF obtained by microsphere studies was also good (r = 0.93). CONCLUSION: rMBF can be measured robustly by factor analysis using dynamic myocardial H2(15)O PET images without additional C15O blood-pool PET.

Animals↗
PubMed1998

Structural equation modeling and its relationship to multiple regression and factor analysis.

Using a conceptual and nontechnical approach, the meaning of structural equation modeling (SEM) and the similarities to, and differences from, more commonly used procedures such as correlation, regression, path analysis, and factor analysis are explained. Application of the statistical technique is presented using data from a study of the relationships among stresses, strains, and physical health in a random sample of 492 community-dwelling elders aged 65 and older. Advantages of each statistical procedure are described. Theoretical issues related to the use of each procedure are presented with emphasis on the need for a sound theoretical model and match between the statistical procedure and the aims of the analysis.

Aged↗
PubMed1984

Identification of patients at high risk for complications of intraaortic balloon counterpulsation: a multivariate risk factor analysis.

Risk factors for vascular complications of intraaortic balloon (IAB) counterpulsation were evaluated in 206 consecutive patients. The approach was percutaneous in 105 patients and surgical cutdown in 101. Vascular complications occurred in 42 patients, and of these 21 required surgery. Multivariate analysis demonstrated the following major risk factors for vascular complications: preexisting peripheral vascular disease (PVD) defined as a history of claudication, femoral bruit or absent pedal pulse (p less than 0.01); and the use of the percutaneous approach (p = 0.02). Evidence of PVD was particularly predictive of major vascular complications requiring surgery (p less than 0.01). In patients with evidence of previous PVD, the risk for a major vascular complication was 31% with the percutaneous, and 16% with the surgical cutdown approach. Without PVD, the risk for a major vascular complication was 4 times higher in women (15%) than in men (3.5%), but in the presence of PVD gender had no significant effect (p = 0.03). Age, duration of IAB counterpulsation and indication for insertion were not significant risk factors. It is concluded that (1) without previous PVD, women are at greater risk than men for major vascular complications (due to smaller arterial size); and (2) evidence of previous PVD identifies patients at high risk for major vascular complications with IAB counterpulsation, particularly by way of the percutaneous approach.

Assisted Circulation↗
PubMed1994

Factor analysis of symptom subtypes of obsessive compulsive disorder and their relation to personality and tic disorders.

Despite advances in our understanding of the pathology and genetics of obsessive compulsive disorder (OCD) and in our ability to successfully treat patients with medications and behavioral psychotherapy, the identification of homogeneous subgroups of patients with OCD has remained elusive. Once identified, such subgroups may be found related to treatment response, biological markers, or genetic transmission of OCD. To clarify identification of symptom subtypes, my colleagues and I administered the Yale-Brown Obsessive Compulsive Scale (Y-BOCS) Symptom Checklist to 107 patients with OCD and applied principal components analysis (e.g., factor analysis) to these data. We then examined the correlations between these factor scores and the presence of comorbid tic and personality disorders, which are thought to be related to OCD. We found that three factors, which we named "symmetry/hoarding," "contamination/cleaning," and "pure obsessions," best explained the symptoms of the Y-BOCS Symptom Checklist. Only the first factor was significantly related to comorbid obsessive compulsive personality disorder or to a lifetime history of Tourette's syndrome or chronic tic disorder. Implications of these findings regarding possible clinical utility are discussed.

Adolescent↗
PubMed2006

Confirmatory factor analysis of the three-factor structure of the schizotypal personality questionnaire and Chapman schizotypy scales.

We examined the factor structure of the Schizotypal Personality Questionnaire (SPQ; Raine, 1991), using confirmatory factor analysis in 3 experiments, with an aim to better understand the construct of schizotypy. In Experiment 1 we tested the fit of 2-, 3-, and 4-factor models on SPQ data from a normal sample. The paranoid 4-factor model fit the data best but not adequately. Based on the strong basis for the Raine 3-factor model we attempted to improve the fit of the 3-factor model by making 3 modifications to the Raine model. These modifications produced a well-fitting model. In Experiment 2 the good fit of this modified 2-factor model to SPQ scores was replicated in an independent normal sample. In Experiment 3, the modified 3-factor model was successfully extended to include the 3 Chapman schizotypy scales. Together these 3 experiments indicate that the 3-factor model of the SPQ, albeit with some slight modifications, is a good model for schizotypy structure that is not restricted to 1 measure of schizotypal personality traits.

Adolescent↗
PubMed2003

Validation of Rome II criteria for functional gastrointestinal disorders by factor analysis of symptoms in Asian patient sample.

BACKGROUND: It has been unclear as to whether the Rome II criteria could be applied to patients in the Asia region with functional gastrointestinal (GI) diseases. The aim of the present study was to determine if symptoms of Asian patients with functional gastrointestinal disorders formed groups which corresponded to the Rome II diagnostic criteria. METHODS: A modified English version of Talley's bowel disease questionnaire was developed in collaboration with various research teams in accordance with the Rome II criteria. This instrument was translated into the local languages of the following nine Asian regions: China, Hong Kong, Indonesia, Korea, Malaysia, Singapore, Taiwan, Thailand and Vietnam. From September to December 2001, newly enrolled outpatients attending 14 GI or medical clinics in these regions were invited to complete the questionnaire. From these respondents, patients with functional gastrointestinal disorders fulfilling the '12 weeks out of 12 months' criteria were separated for further analysis. Principal component factor analysis with varimax rotation was used to identify symptom clusters or factors. These factors were compared with the existing classification of functional GI diseases derived from the Rome II criteria. RESULTS: Factor analysis of symptoms from 1012 functional GI patients supported the Rome II classification of the following groups of functional GI disorders: diarrhea-predominant irritable bowel syndrome, functional constipation, functional dyspepsia, functional abdominal pain syndrome, functional heartburn, and functional vomiting. Functional diarrhea was combined with functional anorectal disorders, and globus merged with functional dysphagia into one factor. Some of the functional dyspepsia, abdominal bloating and belching symptoms were loaded into one factor. CONCLUSIONS: Factor analysis of symptoms from a sample of Asian patients with functional GI disorders partially supported the use of the Rome II classification.

Asia↗
PubMed2006

Generalized five-dimensional dynamic and spectral factor analysis.

We have generalized the spectral factor analysis and the factor analysis of dynamic sequences (FADS) in SPECT imaging to a five-dimensional general factor analysis model (5D-GFA), where the five dimensions are the three spatial dimensions, photon energy, and time. The generalized model yields a significant advantage in terms of the ratio of the number of equations to that of unknowns in the factor analysis problem in dynamic SPECT studies. We solved the 5D model using a least-squares approach. In addition to the traditional non-negativity constraints, we constrained the solution using a priori knowledge of both time and energy, assuming that primary factors (spectra) are Gaussian-shaped with full-width at half-maximum equal to gamma camera energy resolution. 5D-GFA was validated in a simultaneous pre-/post-synaptic dual isotope dynamic phantom study where 99mTc and 123I activities were used to model early Parkinson disease studies. 5D-GFA was also applied to simultaneous perfusion/dopamine transporter (DAT) dynamic SPECT in rhesus monkeys. In the striatal phantom, 5D-GFA yielded significantly more accurate and precise estimates of both primary 99mTc (bias=6.4 % +/- 4.3 %) and 1231 (-1.7% +/- 6.9%) time activity curves (TAC) compared to conventional FADS (biases = 15.5% +/- 10.6% in 99mTc and 8.3% +/- 12.7% in 123I, p < 0.05). Our technique was also validated in two primate dynamic dual isotope perfusion/DAT transporter studies. Biases of 99mTc-HMPAO and 123I-DAT activity estimates with respect to estimates obtained in the presence of only one radionuclide (sequential imaging) were significantly lower with 5D-GFA (9.4% +/- 4.3% for 99mTc-HMPAO and 8.7% +/-4.1% for 123I-DAT) compared to biases greater than 15% for volumes of interest (VOI) over the reconstructed volumes (p < 0.05). 5D-GFA is a novel and promising approach in dynamic SPECT imaging that can also be used in other modalities. It allows accurate and precise dynamic analysis while compensating for Compton scatter and cross-talk.

Algorithms↗
PubMed2000

Students' perceptions of their self-regulatory and other-directed study strategies: a factor analysis.

Edited items on the 24-item Self-efficacy for Self-regulated Learning Scale were combined with 7 items on external regulation developed in 1992 by Vermunt. The inventory was administered to 244 entering freshmen enrolled in a university orientation course. 19 students with incomplete responses were excluded from analysis. Exploratory factor analysis with promax rotation indicated the five factors of general organization and planning, external regulation, typical study strategies, environmental restructuring, and recall. Coefficients alpha were .87, .68, .74, .74, and .73, respectively.

Adolescent↗
PubMed2003

An SAS/IML procedure for maximum likelihood factor analysis.

Maximum likelihood factor analysis (MLFA), originally introduced by Lawley (1940), is based on a firm mathematical foundation that allows hypothesis testing when normality is assumed with large sample sizes. MLFA has gained in popularity since Jöreskog (1967) implemented an iterative algorithm to estimate parameters. This article presents a concise program using matrix language SAS/IML with the optimization subroutine NLPQN to obtain MLFA solutions. The program is pedagogically useful because it shows the step-by-step computational processes for MLFA, whereas almost all other statistical packages for MLFA are in "black boxes." It is also demonstrated that this approach can be extended to other multivariate methods requiring numerical optimizations, such as the widely used structural equation modeling. Researchers may find this program useful in conducting Monte Carlo simulation studies to investigate the properties of multivariate methods that involve numerical optimizations.

Algorithms↗
PubMed1989

[Clinical applications of factor analysis in nuclear medicine].

Factor analysis allows to break up dynamic radionuclide studies into constituent parts corresponding to individual compartments of the distribution space of the radiopharmaceutical in the body. Compartment structure is reflected by factor image and its dynamics is shown by factor time activity curves. The method overcomes the drawbacks of other data processing methods in dynamic scintigraphy by its objectiveness and by distinguishing the projection overlap of tissues with different dynamics. The demands on both the patient and personnel are the same as in standard procedures, yet this method extracts more information from the results of the examination. Higher diagnostic accuracy was reported especially in nuclear cardiology and nephrology. A short survey of clinical applications of factor analysis reported over the years 1982-1988 is presented.

Factor Analysis, Statistical↗
PubMed1999

Positive and negative affectivity in children: confirmatory factor analysis of a two-factor model and its relation to symptoms of anxiety and depression.

The positive affect (PA) and negative affect (NA) framework that is embodied in the tripartite model of anxiety and depression has proved useful with adult populations; however, there is as yet little investigation with children concerning either the measurement of PA and NA or the relation between PA and NA and levels of adjustment. A confirmatory factor analysis was used in this study to examine the structure of self-reported affect and its relation to depressive and anxious symptoms in school children (4th to 11th grade). Results supported a 2-factor orthogonal model that was invariant across age and sex. Support for the expected pattern of relations between NA and PA with symptoms of depression and anxiety was strong for the older sample (M = 14.2 years) but weaker for the younger sample (M = 10.3 years). Results also provide preliminary support for the reliability and validity of the Positive and Negative Affect Schedule for children.

Adolescent↗