## What is/are Squares Analysis?

Squares Analysis - Descriptive statistics and Pearson's chi-squares analysis were used to analyze the data and observe the association between outcome (KAP level) and predictor variables (sociodemographic characteristics).^{[1]}A partial least-squares analysis is conducted to have an observation of 83 Indonesian higher education institutions.

^{[2]}Using multi-group partial least-squares analysis, the study shows differences exist in the utility of e-learning within gender and Generations of X, Y, and Z.

^{[3]}Descriptive statistics, chi-squares analysis, ANOVA, and logistic regression were used to describe ACEs by race and gender and to identify associations between ACEs and onset of aggression, arrest, and psychiatric hospitalization.

^{[4]},To validate a research model for perceived informational support, perceived emotional support and perceived esteem support, the authors conducted a partial-least-squares analysis of empirical data from an online survey (N = 173) of users of two smoking cessation OHCs.

^{[5]}Data were subjected to least-squares analysis of variance using the General Linear Models procedure of SAS (SAS Institute Inc.

^{[6]}Data on birth weight, preweaning daily rate of gain and weaning weight of Ndama beef cattle were obtained from routine records kept on the Fashola Livestock Farm between 1959 and 1964 and subjected to least-squares analysis to determine the effect of sex, month, year and sire on the performance characteristics.

^{[7]}Fourteen hand models were obtained by the PCA, while three, five, and nine archetypal analysis k-value were selected after a root sum of squares analysis for k = 1,…, 12 archetypes.

^{[8]}The least-squares analysis, robust regressions, statistical parametric and non-parametric tests are conducted to analyze the data.

^{[9]}Using PCR-RFLP method and direct sequencing, noticed a single-nucleotide polymorphism in exon3 region of the Prolactin gene in 156bp and also the effect of non- genetic factors on each trait was assessed by least-squares analysis for non-orthogonal data by a fixed model.

^{[10]}By partial-least-squares analysis, T2DM duration, baseline HbA1c, and ensuing insulin therapy were the strongest predictors of remission.

^{[11]}The effect of non-genetic factors on seminal parameters was analyzed using least-squares analysis of variance under general linear model.

^{[12]}Using multivariate partial-least-squares analysis, we observed a significant pattern revealing positive associations of striatal as well as extrastriatal DA D2/3 receptors to BOLD response in the thalamo–striatal–cortical circuit, which supports WM functioning.

^{[13]}These trends were subject to sequential sum of squares analysis to examine whether annual increases in mean BMI and obesity prevalence estimates diminished or were maintained over the 2002 to 2015 period.

^{[14]}We conducted analysis of covariance with potential confounders (body mass index, age, sex) as covariates and partial least-squares analysis.

^{[15]}Eventually, more accurate parameters are obtained by a non-linear least-squares analysis of the simple nutation experiment.

^{[16]}Recently, a nonlinear least-squares analysis (NLS) algorithm was proposed to overcome the limitation of the wavelength scanning range to achieve super-resolution; however, the NLS failed to measure speckle surfaces owing to the sensibility of initial values.

^{[17]}To access the degree to which natural fractures can be predicted based on chemical composition, we applied a partial least-squares analysis, a multivariate method, and recorded an r2 1⁄4 0.

^{[18]}Several deconvolution methods, including positive matrix factorization, parallel factor analysis, and least-squares analysis, were applied to the measured spectra, resulting in three classes of WSOM.

^{[19]}As a by-product of the proposed method, a de-speckled pseudo-span image, which is obtained from the least-squares analysis of the de-speckled multi-polarization channels, is also produced.

^{[20]}The TPP-2M formula, however, poorly describes several materials because it relies heavily on the traditional least-squares analysis.

^{[21]}Data were collected from 2,67,599 daily milk yield (DMY) records of 445 buffaloes from 2001 to 2016 and analyzed using fixed linear least-squares analysis.

^{[22]}The sub-squares analysis will be used to analyze the surveys.

^{[23]}For grade discrimination, we determined grade prediction models for each tea type by partial least-squares analysis; the coefficients of determination of the prediction models were both above 0.

^{[24]}

## orthogonal partial least

Differential serum and urine metabolic profiles between the pre- and post-training group were obtained on gas chromatography coupled to mass spectrometry (GC-MS) and data subsequently underwent orthogonal partial least-squares analysis (OPLS).^{[1]}After successful classification, visualization tools of robust principal component analysis and orthogonal partial least squares analysis were explored to uncover fingerprints of unusual (atypical and spiked) paprika powders.

^{[2]}For the annotated metabolites, we created statistically significant models for storage time prediction for all storage conditions by orthogonal partial least squares analysis, using storage time as the y-variable.

^{[3]}Using bidirectional orthogonal partial least squares analysis, 19 bacterial genera were identified as core functional genera linked to the metabolism of chemical compounds during the manufacturing process, while three genera, namely Klebsiella, Lactococcus, and Bacillus, also dominated the Fu brick tea fermentation process.

^{[4]}Statistical analysis was conducted using principal component analysis (PCA) and orthogonal partial least-squares analysis (OP-LSDA).

^{[5]}ANOVA (analysis of variance) and orthogonal partial least squares analysis (OPLS) identified 20 metabolites as tentative biomarkers of Colletotrichum theobromicola infection (e.

^{[6]}

## multivariate curve resolution

The kinetic of the photodecarbonylation has been elucidated by multivariate curve resolution alternating least‐squares analysis.^{[1]}The role of each initial IND crystal state (γ-form, α-form, amorphous) was explored using Raman spectroscopy with multivariate curve resolution by alternating least-squares analysis (MCR-ALS) as a chemometrics, X-ray diffraction, and tablet dissolution testing.

^{[2]}Variations in the band due to O–H stretching vibration overtones of water and alcohol with changes in concentration and temperature were determined by a multivariate curve resolution-alternating least squares analysis, which identified the components of the band causing the spectral variation.

^{[3]}

## two stage least

Based on these innovation data, this study conducts two-stage least squares analysis that considers the time-lag effect.^{[1]}A fixed effects two-stage least squares analysis is conducted to investigate the determinants of environmental income and a quantile regression shows the distribution of effects.

^{[2]}Two-stage least squares analysis highlights that child labor undermines academic achievement regardless of subject, gender, and age.

^{[3]}

## Least Squares Analysis

Based on partial least squares analysis (PLS) which is a model fitting based on validity and reliability analysis, the results showed that macro data volume, macro data speed, and macro data variability are based on three criteria of e-government implementation ie e-government core.^{[1]}Impacts were compared by using the Generalized Least Squares analysis.

^{[2]}Effective wavelengths were selected using regression coefficients based on partial least squares analysis.

^{[3]}Weighted, non-linear least squares analysis was used to determine the parameters from the data sets and Monte-Carlo simulations were utilized to obtain estimates of the error.

^{[4]}Three-stage least squares analysis was employed in the empirical investigation.

^{[5]}Afterwards, Partial Least Squares analysis (PLS) indicated lycorine and 11,12-dehydro-2-methoxy-assoanine as the compounds responsible for the anti-inflammatory activity of the bioactive fraction.

^{[6]}We relate variations in model performance with environmental completeness, data characteristics, and species traits through a partial least squares analysis.

^{[7]}Partial least squares analysis identified one significant latent variable (accounting for 59.

^{[8]}The partial least squares analysis on 223 giver-users and 335 giver-non-users showed that bonding and bridging social capital encourage giver-non-users to use the apps.

^{[9]}A mul-tivariate least squares analysis was used to identify a series of equations that would serve to project state insecurity, both in terms of homicide and car theft.

^{[10]}The partial least squares analysis was used to test the model validity for this consumer group.

^{[11]}To fit and test the research hypothesis, partial least squares analysis was used.

^{[12]}To achieve this goal, we apply structural equation modelling based on partial least squares analysis (PLS).

^{[13]}Based on the results of an online survey in three cities of Taiwan, we empirically test the research model using partial least squares analysis.

^{[14]}The growth performance was analyzed by least squares analysis and information on reproduction parameters of Chaugarkha goats was generated.

^{[15]}Design/methodology/approachStructural equation modelling with partial least squares analysis has been applied.

^{[16]}Data were analysed using General Linear Model of least squares analysis of variance to test the influence of genetic group, sex, season and age on weights and linear body measurements such as height at withers (HT), body length (BL), Neck length (NL), Neck circumference (NC), heart girth (HG), Foreleg length (FL), Hind leg length (HL), Face length (FA), Ear length (EA), Headwidth (HW), shoulder width (SW), tail length (TL) and Rump height (RH).

^{[17]}We use a combination of scanning electron microscope (SEM) observation, dietary composition analysis (stomach observation, trophic niche amplitude, trophic overlap, and feeding strategy), and geometric morphometric tools (discriminant analysis and two-block partial least squares analysis).

^{[18]}An ordinary least squares analysis was used to model differences between event types.

^{[19]}The associations between electrophysiological spectral signatures and each child's neurocognitive profiles were characterized using a partial-least squares analysis.

^{[20]}Testing constructs from the Unified Theory of Acceptance and Use of Technology 2 and environmental awareness, partial least squares analysis was performed with the software SmartPLS to investigate a dataset of 224 respondents.

^{[21]}In the partial least squares analysis, decreases in fasting insulin and in estimated insulin resistance were associated with the observed increase in MR‐proANP concentrations.

^{[22]}Partial least squares analysis combined behavioural performance, ERPs, and/or event-related EEG band power (ERBP).

^{[23]}If required, a straight directional well path, may also be derived through a linear approximation to the optimised non-linear trajectory by least squares analysis.

^{[24]}Partial least squares analysis showed that 40.

^{[25]}Direct classical least squares analysis further identified the relative abundances of the three major components of the single particles: soot (69.

^{[26]}Findings The empirical results are based on partial least squares analysis and statistical package for the social sciences.

^{[27]}Partial Least Squares analysis shows a) that 41.

^{[28]}Partial least squares analysis showed that 69.

^{[29]}Based on these innovation data, this study conducts two-stage least squares analysis that considers the time-lag effect.

^{[30]}Phylogenetic signal was tested using the K statistics and associations between morphology and environmental variables were made using a phylogenetic partial least squares analysis.

^{[31]}A two-block partial least squares analysis 2B-PLS highlighted differences in biodiversity indices and structural traits between the two forest ecosystems.

^{[32]}A fixed effects two-stage least squares analysis is conducted to investigate the determinants of environmental income and a quantile regression shows the distribution of effects.

^{[33]}A least squares analysis of the ab initio functions at large internuclear distances in conjunction with long-range perturbation theory (LRPT) revealed three different asymptotic behaviors of the LΠΣ(R → +∞)-functions: const.

^{[34]}Linear calibration models with high R², low error and high ratio of performance to deviation values were observed from partial least squares analysis for different wood properties.

^{[35]}A total of 394 hyperfine components were measured and subjected to a least squares analysis which allowed determining twelve hyperfine constants for nitrogen and deuterium nuclei.

^{[36]}Survey data collected from 176 employees of several banks in Mongolia were used to test our model by using partial least squares analysis.

^{[37]}Using a predictor-corrector procedure that fits real climatic data to a continuous periodic function, we demonstrate how climatic variables can be included in the model and how models for the time variation of temperature and precipitation in a given area can be constructed just by appropriately choosing the parameters of a sinusoidal function and then correcting the output using nonlinear least squares analysis.

^{[38]}An ordinary least squares analysis was used to model differences between event types.

^{[39]}Partial least squares analysis on data from 355 individuals who have never visited London (196 and 159 under tWOM and sWOM scenarios, respectively) shows leisure constraints exhibit restraining (with lack of interest contributing negatively to sWOM recommendations) and enabling (with lack of time contributing positively to tWOM recommendations) potential as recommendation motivators.

^{[40]}Discriminant partial least squares analysis further identified optimum biochemical modulations in the shoots of PKV AKM 12-28 and 75 mM NaCl.

^{[41]}A multivariate Partial Least Squares analysis revealed patterns of neural overlap between memory and problem solving during the generation phase that were distinct from the elaboration phase.

^{[42]}A partial least squares analysis of network data in a medium-sized company (N = 343) offers evidence of an effect of the relational dimension (tie strength), through social support.

^{[43]}Statistical models and machine learning regression algorithms, including ordinary least squares analysis, generalized linear and generalized additive models, and support vector regression were utilized to model the occurrence of DF over a long period.

^{[44]}After successful classification, visualization tools of robust principal component analysis and orthogonal partial least squares analysis were explored to uncover fingerprints of unusual (atypical and spiked) paprika powders.

^{[45]}Additionally, using a partial least squares analysis the relationship between spatiotemporal parameters of gait and the margins of stability was explored in both groups.

^{[46]}In combination with partial least squares analysis and Procrustes transformation, these PMF descriptors were employed successfully to develop correlations that predict the activities of target protein inhibitors involved in various diseases (cancer, neurodegenerative disorders, HIV, and malaria).

^{[47]}Phylogenetic generalized least squares analysis showed plant phylogeny weakened the relationships between species traits vs.

^{[48]}The latter may be trained, tested and validated with Partial Least Squares analysis.

^{[49]}This research uses a quantitative approach with SEM Partial Least Squares analysis method.

^{[50]}

## squares analysis revealed

The least-squares analysis revealed that the season of calving, period of calving, and parity affected several production and reproduction traits of Vrindavani cows significantly.^{[1]}A multivariate Partial Least Squares analysis revealed patterns of neural overlap between memory and problem solving during the generation phase that were distinct from the elaboration phase.

^{[2]}Additionally, multi-group comparisons in partial least squares analysis revealed partial but statistically significant differences in the path relationships between male customers (568) and female customers; (485); foreign (465) and domestic (588) customers, among night market visitors.

^{[3]}Least squares analysis revealed that Barbari goats showed significantly higher average litter size (2.

^{[4]}Odds ratio and least squares analysis revealed a significant association ( P < 0.

^{[5]}Further, the least squares analysis revealed non significant effect of season of calving and age at first calving groups on all first lactation reproduction and milk production traits.

^{[6]}

## squares analysis showed

The least-squares analysis showed a significant association (p < 0.^{[1]}Partial least squares analysis showed that 40.

^{[2]}Partial least squares analysis showed that 69.

^{[3]}Phylogenetic generalized least squares analysis showed plant phylogeny weakened the relationships between species traits vs.

^{[4]}Least-squares analysis showed that the slope and intercept of the regression line are 1.

^{[5]}

## squares analysis indicated

Partial least squares analysis indicated that precipitation was high between sowing and 3rd leaf was determinant for yield, and a negative correlation between these variables was observed.^{[1]}Least squares analysis indicated that effect of gender, month of hatch and generation were significant (p less than 0.

^{[2]}Statistical testing using the mean-centered Partial Least Squares analysis indicated periods where a given visual or auditory stimuli had higher activation.

^{[3]}

## squares analysis show

Partial Least Squares analysis shows a) that 41.^{[1]}On the contrary, the results of the partial least squares analysis shows a strong association between the shape changes in the maxilla with changes in the pattern of bone modeling in both groups of age, subadults and adults.

^{[2]}

## squares analysis method

This research uses a quantitative approach with SEM Partial Least Squares analysis method.^{[1]}Pooled Least Squares analysis method was used.

^{[2]}

## squares analysis identified

Partial least squares analysis identified one significant latent variable (accounting for 59.^{[1]}Partial least squares analysis identified possible correlations between sensory attributes and volatile compounds.

^{[2]}