SEM Path Analysis Causal Model

@belarjsoufiane20

I understand you’re looking for a theory-driven Path Analysis that stays true to your conceptual framework rather than relying on unnecessary model modifications. I’ll build the model, estimate the relationships, evaluate the fit, and provide clear, reproducible results with concise interpretations. A couple of quick questions: 1. Which SEM software would you like me to use (R lavaan, AMOS, Mplus, or another)? 2. Does your model include latent variables, or is it a path analysis using only observed variables?

@nrajuu07

I'm a quantitative researcher with hands-on experience specifying and estimating structural equation models and path analyses in R lavaan and Mplus, always working from theory first rather than modification-index fishing. I'll take your conceptual diagram and dataset, build a fully specified path model, and deliver reproducible syntax, complete output tables with standardized and unstandardized estimates, standard errors, p-values, and all fit indices including χ², CFI, TLI, RMSEA, and SRMR, a publication-ready path diagram, and a clear 1 to 2 page memo explaining the causal interpretations and any modification indices considered. One iteration on model fit is built into the workflow. Relevant SEM work samples available immediately.

@citijayamala

1. I am an expert in Statistics, Regression analysis, Linear regression analysis, p value, ANOVAs, etc. I use excel and other statistical software like SPSS, STATA, E-views for data analysis and statistical analysis based on client requirement. 2. Have done many projects in statistics using SPSS, STATA, E-views. I read your project and sure I can handle your project. 3. Your project will be delivered on time with high standard 4. Assistance will be provided with number of clarifications until client satisfaction 5. I will provide assistance even after the payment. And will maintain data (content) security. Please connect in chat for more discussion, Regards, Jaya

@EhtishamHaider1

As an experienced data scientist, I carry a strong track record in untangling complex data structures, transforming raw datasets into actionable insights, and presenting them in an easily-digestible visual form that adheres to academic and industry standards. Combined with my proficiency in SAS, STATA, SPSS and AMOS for statistical modeling and reporting, this makes me the ideal candidate for your SEM path analysis causal model. Drawing from my deep knowledge of multiple programming languages, including Python, R, MATLAB, I will meticulously script your conceptual framework into a structured syntax that can be consistently reproduced. Utilizing tools like Power BI, Google Sheets, KNIME etc., I will provide not just the filled-in output tables necessary to quantify the causal relationships but also a precise and publication-ready visuals suitable for inclusion in your work. Having completed numerous successful projects involving SEMs and path analysis previously, replete with a clear exposition on causal interpretations and modification indices (as you expect back), I am well aware of the challenges unique to this domain. Rather than resorting to data-dredging, my approach will strictly adhere to the theoretically-driven paths indicated by your framework.

@anumali0987

With over 500 academic research projects under my belt, I have an extensive background in conducting sophisticated data analysis for various disciplines. Specifically, your project requirements align greatly with my proven prowess in Structural Equation Modeling (SEM) using R, Mplus, AMOS, or equivalents as well as the delivery of detailed output tables and visually appealing path diagrams. My past works have included the very elements you seek — standardized/unstandardized estimates, fit indices including χ2, CFI, TLI, RMSEA, SRMR and robust causal interpretations.

@alluankit01

Hi, I can build and interpret your SEM path analysis model using your conceptual diagram, labelled CSV dataset, and codebook. The best solution is to first review your theoretical framework, observed/latent variables, measurement structure, hypothesized causal paths, sample size, and variable coding. I’ll then specify the model in R lavaan or another preferred SEM tool, estimate the path coefficients, review model fit, and prepare clean output tables and a publication-ready path diagram. I’m comfortable with SEM, path analysis, R lavaan, AMOS/Mplus-style workflows, standardized and unstandardized estimates, p-values, fit indices, modification indices, statistical reporting, and visual model diagrams. Deliverables will include: * Reproducible SEM script/syntax * Full path analysis model * Standardized and unstandardized estimates * Standard errors and p-values * χ², CFI, TLI, RMSEA, and SRMR * Publication-style path diagram * Brief 1–2 page interpretation memo * Notes on modification indices * One model-fit iteration if needed I’ll focus on theoretically driven modelling, clear causal interpretation, and clean outputs that are easy to reproduce and include in your report or publication. Best regards Ankit

@rakhshanz3

As an AI specialist and data scientist with extensive experience in developing advanced models, I am well-equipped to tackle your SEM Path Analysis Causal Model project. My academic background in Computer Science, alongside my PhD in Artificial Intelligence, provides me with a strong fundamental foundation for conducting complex analyses like SEM path analysis. Throughout my 20-year career, I've applied statistical methods and programming languages such as R lavaan, Mplus, AMOS, and more to deliver precise solutions. My experience includes not just creating syntax or scripts for models but also generating comprehensive output tables tailored to meet clients' specific requirements - standardized estimates, unstandardized estimates, p-values, standard errors, fit indices like χ², CFI, TLI, RMSEA, SRMR - will all be covered. Additionally, my proficiency extends to producing easily interpretable visualizations perfect for publication. On top of this, you can expect a concise memo from me on all major causal interpretations as well as any modifications considered. To illustrate the approach I would take with your project and the quality of my work overall, I have attached a sample of a past SEM analysis I've conducted."

@tnowsolutions

Hello, I can build and estimate your Structural Equation Model using path analysis in R (lavaan), including standardized/unstandardized coefficients, standard errors, p-values, direct and indirect effects, and all requested fit indices. I will also provide reproducible syntax, publication-ready output tables, a clean path diagram, and a concise interpretation memo. I will begin strictly from your theoretical framework and only review modification indices where they are statistically and conceptually justified. One model-fit revision is included. Regards,

@sanddep5

As a well-rounded and experienced Data Analyst with a penchant for detail, I assure you that my skills align perfectly with the SEM Path Analysis Causal Model project you proposed. While my expertise lies in Full-Stack Development and UI/UX Design, I have a long-standing passion for leveraging data to generate meaningful insights. These attributes perfectly position me to create the precise structural equation model you require. My proficiency in data analysis, using tools such as R lavaan, Mplus, AMOS, has not only allowed me to effectively navigate complex datasets but also to provide thoroughoutput analyses. These include all standard measurements you require - standardized and unstandardized estimates, p-values, fit indices (χ², CFI, TLI, RMSEA, SRMR). Not to mention a tidy visual path diagram suitable for publication. Moreover, with agile thinking comes an eagerness for iterations yet understanding of the need for theoretically driven paths over data-dredging. Completing these projects on-time without sacrificing quality is something I specialize in. Lastly, while my past work samples demonstrate my capabilities effectively analyzing similar models as yours', I'd love an opportunity to discuss previous projects in more depth during the selection process.

@priyam804

Hello, I can help you build a Structural Equation Model (SEM) focused on Path Analysis using your conceptual framework and dataset. I will develop the model based on theory, provide the complete syntax, output tables with fit indices, a publication-ready path diagram, and a clear summary of the results. I pay close attention to accuracy and will work with you to refine the model if needed. I look forward to discussing your project and helping you achieve reliable results.

@wilmerae

Hello. I can help you develop and evaluate your Structural Equation Model with a focus on theoretically driven path analysis and clear interpretation of causal relationships. As I understand it, you already have the conceptual framework, variables, and dataset, and you need a reproducible SEM workflow including model specification, estimation, statistical output, visualization, and a concise interpretation report. I have experience with statistical analysis, data modeling, R-based workflows, and quantitative research methods. I can create a complete SEM script using R lavaan or another suitable tool, generate standardized and unstandardized estimates, significance testing, fit indices, and a publication-ready path diagram. My approach will include: 1. Translating your conceptual framework into a properly specified SEM path model. 2. Preparing and validating the dataset according to the supplied codebook. 3. Running the model estimation and reporting key fit measures including χ², CFI, TLI, RMSEA, and SRMR. 4. Reviewing modification indices carefully while maintaining theoretical consistency. 5. Providing documented scripts, output tables, visual diagrams, and an interpretation memo. I will focus on producing a reproducible analysis that clearly explains the relationships in your model rather than relying on data-driven adjustments. I hope we can create a great project together.

@bhargav922002

Hello, I'm bharghav, with 10 years of experience in Machine Learning and R Programming Language, specializing in complex statistical modeling. I understand you need a Structural Equation Model with a focus on Path Analysis to quantify causal relationships. I will use R with the lavaan package to specify and estimate your model, adhering to your conceptual diagram and dataset. You'll receive reproducible R script, full output tables, a publication-ready path diagram, and a memo explaining causal interpretations and modification indices. Please initiate a chat so we can discuss your project further and clarify any details. Best regards,

@allimains

Hi, I’m interest in working in this project and do SEM analysis. I ever do SEM analysis and published it on Oct, 2014. I collect data using survey on Diponegoro University to measure student satisfaction. I couldn’t find my file but you can search it using keywords “SEM I would be happy to re-learn again about this method and deliver the analysis result to you. Lets discuss about it. Best Regards, Allima

@VowDev

You need a theory-driven SEM path analysis — not data-dredging, but a model that reflects the causal relationships in your conceptual framework. I understand the distinction matters. What I'll deliver: - A clean, reproducible R lavaan script specifying the full model based on your conceptual diagram and codebook. I'll start with your theoretically driven paths and flag any modification indices worth discussing. - Full output tables: standardized and unstandardized estimates, standard errors, p-values, and all key fit indices (chi-square, CFI, TLI, RMSEA, SRMR). - A publication-ready path diagram with coefficients. - A 1-2 page memo covering causal interpretations, model fit assessment, and any modification indices considered. Happy to iterate on model fit once you review the initial results. If there's a specific journal or formatting standard you're targeting, let me know and I'll match it. One question: does your conceptual framework include any mediating or moderating variables, or is this a straightforward direct-effects path model?

@badrez2

Hi there, Your brief is unusually clear — you want the causal paths in your conceptual framework quantified cleanly, with the model driven by theory, not by chasing modification indices until the fit passes. That's exactly how we'd approach it: we specify your diagram as-is (measurement model for the latents, structural model for the causal paths), estimate it, and report honestly. You'll get a fully reproducible lavaan project: a parameterized, commented script that runs end-to-end on your .csv; complete tables (standardized + unstandardized estimates, SEs, p-values, CIs, endogenous R²) and every fit index you listed (χ² with df, CFI, TLI, RMSEA with 90% CI, SRMR); a publication-ready vector path diagram; and a 1–2 page memo interpreting effects and documenting any MI we considered — with paths kept theory-first. We build reproducible analytical pipelines with locked dependencies, clean structured exports and guaranteed reruns — happy to share a repo showing that standard. We've also prepared a working proof-of-concept for your model shape. Plan: script + estimation (2 days) → full tables & path diagram (day 3) → memo + one fit-iteration round (day 4). We can milestone payment across those four phases. Two quick questions to lock the estimator and specification: are your indicators continuous or ordinal/Likert (ML vs WLSMV)? And does your framework include mediation to decompose (bootstrapped indirect effects)? Also — lavaan, or do you need Mplus/AMOS specifically? Looking forward to it.

@HafizMArhamAli

Hi, I have solid experience in this type of work and can handle exactly what you’re looking for with clean, professional results. I focus on delivering high-quality work, meeting deadlines, and ensuring everything aligns perfectly with your expectations. Although I’m new on Freelancer and don’t have reviews here yet, I have real hands-on experience from other platforms and projects. So please don’t underestimate my capability based on that. If you’d like, I’m happy to prove my skills with a quick test task before we proceed. I’m ready to get started and can easily adapt to your requirements or preferred style. Let’s connect in chat to discuss the details and finalize the scope. Looking forward to working with you. Thanks,

@Abrotab

I am delighted to share my qualifications for your SEM Path Analysis Causal Model project. With a deep understanding of relevant statistical methods, especially employing the R Lavaan package for Structural Equation Modeling, I can analyze and clearly quantify causal relationships as outlined in your conceptual framework. Additionally, as a professional with significant experience in data analysis and visualization, I can transform your raw dataset into comprehensive and visually impactful outputs that will help you understand the dynamics of these complex relationships. Previous clients have lauded my ability to simplify complicated findings without losing technical accuracy - a skill I will utilize towards ensuring your publication-worthy visual path diagram is both comprehensible and scientifically rigorous. Likewise, my proficiency in interpreting standard errors, p-values, RMSEA and other key fit indices will contribute to the efficiency of the final model. Lastly, my focus on using theory-driven paths over data-dredging fits well with your requirement to begin with theoretically driven paths thus making me an ideal partner for the iterative aspect of this project that should result in a robust and reliable SEM model for you. I am excited about the possibility of working with you and look forward to leveraging my expertise into meaningful deliverables that drive decision-making for your organization.

@shayankhan333

Starting from theoretically driven paths before touching modification indices is exactly the right call, it keeps the model interpretable and defensible in peer review. I'll specify the full model in R lavaan, estimate both standardized and unstandardized coefficients, and deliver the complete fit index table (χ², CFI, TLI, RMSEA, SRMR) alongside a publication-ready path diagram using semPlot. One thing worth flagging early: if any of your observed indicators have skewed distributions, I'll switch to MLR estimation instead of standard ML, since non-normal data can inflate χ² and distort standard errors significantly. I've done similar SEM work across research contexts and can share a relevant example in chat. 1) Are any of your variables ordinal or categorical, or is everything continuous? Happy to talk details in chat. Shayan