Limitations of Ordinary Least Squares Models in Analyzing Repeated Measures Data

2004 ◽  
pp. 2144-2148 ◽  
Author(s):  
CARLOS UGRINOWITSCH ◽  
GILBERT W. FELLINGHAM ◽  
MARK D. RICARD
Keyword(s):  
Least Squares ◽  
Repeated Measures ◽  
Ordinary Least Squares ◽  
Repeated Measures Data

The use of MIXED models in the analysis of animal experiments with repeated measures data

2004 ◽  
Vol 84 (1) ◽  
pp. 1-11 ◽  
Author(s):  
Z. Wang and L. A. Goonewardene
Keyword(s):  
Least Squares ◽  
Linear Model ◽  
Repeated Measures ◽  
Mixed Model ◽  
Covariance Structure ◽  
General Linear Model ◽  
Ordinary Least Squares ◽  
General Linear ◽  
Repeated Measures Data ◽  
Split Plot

The analysis of data containing repeated observations measured on animals (experimental unit) allocated to different treatments over time is a common design in animal science. Conventionally, repeated measures data were either analyzed as a univariate (split-plot in time) or a multivariate ANOVA (analysis of contrasts), both being handled by the General Linear Model procedure of SAS. In recent times, the mixed model has become more appealing for analyzing repeated data. The objective of this paper is to provide a background understanding of mixed model methodology in a repeated measures analysis and to use balanced steer data from a growth study to illustrate the use of PROC MIXED in the SAS system using five covariance structures. The split-plot in time approach assumes a constant variance and equal correlations (covariance) between repeated measures or compound symmetry, regardless of their proximity in time, and often these assumptions are not true. Recognizing this limitation, the analysis of contrasts was proposed. If there are missing measurements, or some of the data are measured at different times, such data were excluded resulting in inadequate data for a meaningful analysis. The mixed model uses the generalized least squares method, which is generally better than the ordinary least squares used by GLM, if the appropriate covariance structure is adopted. The presence of unequally spaced and/or missing data does not pose a problem for the mixed model. In the example analyzed, the first order ante dependence [ANTE(1)] covariance model had the lowest value for the Akaike and Schwarz’s Bayesian information criteria fit statistics and is therefore the model that provided the best fit to our data. Hence, F values, least square estimates and standard errors based on the ANTE (1) were considered the most appropriate from among the five models demonstrated. It is recommended that the mixed model be used for the analysis of repeated measures designs in animal studies. Key words: Repeated measures, General Linear Model, Mixed Model, split-plot, covariance structure

Analyzing pre-post randomized studies with one post-randomization score using repeated measures and ANCOVA models

2018 ◽  
Vol 28 (10-11) ◽  
pp. 2952-2974 ◽  
Author(s):  
Fei Wan
Keyword(s):  
Least Squares ◽  
Treatment Effect ◽  
Repeated Measures ◽  
Interaction Model ◽  
Ordinary Least Squares ◽  
Analysis Of Covariance ◽  
Baseline Score ◽  
Sample Mean ◽  
Heterogeneity Of Treatment Effect ◽  
Randomized Studies

The analysis of covariance (ANCOVA) or repeated measures (RM) models are often used to compare the treatment effect between different arms in pre-post randomized studies. ANCOVA adjusts the baseline score as a covariate in regression models. RM treats both the baseline and post-randomization scores as outcome variables. We aim to establish the underlying connections between ANCOVA and a constrained RM (“cRM”). We start with the interrelated concepts in a pre-post randomized designs: homogeneous vs. heterogeneous study populations, the marginal vs. the conditional treatment effect, and homogeneity vs. heterogeneity of treatment effect. We then demonstrate the asymptotic equivalence between the ANCOVA and cRM estimators for the marginal treatment effect and discuss the conditions under which ANCOVA needs to include a baseline score by treatment interaction term. In particular, an ANCOVA interaction model with a mean centered baseline score can assess both the marginal treatment effect and the heterogeneity in the conditional treatment effect. However, the ordinary least squares (OLS)-based inference is not valid for unconditional inference because this interaction model typically has heteroskedastic errors, and ordinary least squares treats the sample mean of the baseline score as a known parameter. We propose a bootstrap and a heteroskedasticity consistent variance estimator for heteroskedastic ANCOVA. Our simulation studies demonstrate that the proposed methods provide valid inferences for testing both the marginal treatment effect and the heterogeneity of treatment effect using an ANCOVA interaction model. We used an acupuncture headache trial to elucidate the proposed approaches.

Probability-Based and Measurement-Related Hypotheses With Full Restriction for Investigations by Means of Confirmatory Factor Analysis

Methodology ◽  
2011 ◽  
Vol 7 (4) ◽  
pp. 157-164
Author(s):  
Karl Schweizer
Keyword(s):  
Factor Analysis ◽  
Confirmatory Factor Analysis ◽  
Cognitive Processing ◽  
Latent Variables ◽  
Repeated Measures ◽  
Latent Variable ◽  
Model Fit ◽  
Repeated Measures Data ◽  
Confirmatory Factor ◽  
And Performance

Probability-based and measurement-related hypotheses for confirmatory factor analysis of repeated-measures data are investigated. Such hypotheses comprise precise assumptions concerning the relationships among the true components associated with the levels of the design or the items of the measure. Measurement-related hypotheses concentrate on the assumed processes, as, for example, transformation and memory processes, and represent treatment-dependent differences in processing. In contrast, probability-based hypotheses provide the opportunity to consider probabilities as outcome predictions that summarize the effects of various influences. The prediction of performance guided by inexact cues serves as an example. In the empirical part of this paper probability-based and measurement-related hypotheses are applied to working-memory data. Latent variables according to both hypotheses contribute to a good model fit. The best model fit is achieved for the model including latent variables that represented serial cognitive processing and performance according to inexact cues in combination with a latent variable for subsidiary processes.

PENGARUH STRUKTUR KEPEMILIKAN BANK TERHADAP KINERJA UNIT USAHA SYARIAH PADA BANK DI INDONESIA

2018 ◽  
Vol 1 (2) ◽  
pp. 25-32
Author(s):  
Hafidzah Nurjannah ◽  
Yul Efnita ◽  
Eva Sundari
Keyword(s):  
Least Squares ◽  
Firm Size ◽  
Ordinary Least Squares

Penelitian ini bertujuan untuk menganalisa pengaruh secara signifikan baik partial maupun simultan pada variabel kepemilikan bank, simpanan (DPK), rasio pinjaman terhadap simpanan (LDR) dan rasio kecukupan modal (CAR), Non Performing Loan (NPL) dan ukuran perusahaan terhadap profitabilitas (ROA) pada bank yang memiliki Unit Usaha Syariah (UUS) baik itu pada Bank Pembangunan Daerah (BPD) maupun Bank Swasta. Populasi dan sampel terdiri dari 24 UUS milik Bank Pembangunan Daerah (BPD) dan Bank Swasta. Dari ke 24 bank tersebut, hanya 18 bank yang dipilih menjadi sampel. Bank-bank tersebut adalah 7 Bank Swasta dan 11 Bank Pembangunan Daerah. Periode penelitian ini adalah 2010-2014. Data diambil dari laporan tahunan bank. Penelitian ini menggunakan data panel dan pooled Ordinary Least Squares (OLS). Hasil penelitian menunjukkan UUS milik Bank Pembangunan Daerah lebih baik daripada Bank Swasta. Hal ini disebabkan beberapa faktor. Pertama, pinjaman hanya untuk pejabat pemerintah daerah di mana pembayaran pinjaman melalui pengurangan gaji, sehingga kemungkinan tidak dapat membayar pinjaman sangat rendah meskipun situasi ekonomi tidak stabil. Kedua, karena Bank Pembangunan Daerah menyediakan layanan hanya untuk lokal saja, sehingga memiliki pengetahuan khusus tentang daerah tersebut. Sehingga akan memungkinkan nasabah menilai penerapan pinjaman dan mengidentifikasi pinjaman yang memenuhi syarat. Ketiga, kinerja Bank Pembangunan Daerah yang diawasi oleh pemerintah daerah lebih intensif. Kata Kunci : Hedging, Laverage, Cash Ratio, Firm Size, Bank Syariah.

The antecedents of corporate social and environmental responsibility discourse in Pakistan: Multiple theoretical perspectives

2019 ◽  
Author(s):  
Muhammad Farhan Basheer ◽  
Saqib Muneer ◽  
Muhammad Atif ◽  
Zubair Ahmad
Keyword(s):  
Institutional Theory ◽  
Least Squares ◽  
Agency Theory ◽  
Stakeholder Theory ◽  
Fixed Effects ◽  
Ordinary Least Squares ◽  
Environmental Responsibility ◽  
Legitimacy Theory ◽  
Discourse Practices ◽  
Corporate Social

The primary purpose of the study is to explore the antecedents of corporate social and environmental responsibilities discourse practices in Pakistan. The industry sensitivity, government shareholding, block holder ownership, print media coverage, environmental monitoring programs, and strategic posture are examined as antecedents of corporate social and environmental responsibility practices. A multidimensional theoretical perspective namely stakeholder theory (ST), institutional theory (IT), agency theory (PAT), and legitimacy theory (LT) is used to conceptualize the phenomena. All the four of perspective theories (positive accounting theory, legitimacy theory, stakeholder theory, and institutional theory) claim that there are ‘pressures’ that impact the organization. How much ‘pressures’ are recognized, managed or satisfied differs from one perspective of theory to the other. To estimate the data, this study uses three sets of panel data models, i.e., the pooled ordinary least squares model (POLS) or constant coefficients model, fixed effects (FEM or least squares dummy variable/LSDV model) and random-effects models. The final sample is comprising of 173 firms over eight years from 2011 to 2017. The firms listed in PSX are included in the sample. Overall the findings of the study have shown agreement with the proposed results. However, the study has provided more support to the institutional theory and stakeholder theory. Keywords: Corporate Social Responsibility, Stakeholders Theory, Agency Theory, Pakistan

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