Subtopic Deep Dive
Research Sampling Techniques
Research Guide
What is Research Sampling Techniques?
Research Sampling Techniques encompass probability and non-probability sampling designs, sample size determination, and error minimization strategies used in empirical studies across quantitative and qualitative research paradigms.
These techniques ensure statistical validity and generalizability of findings by selecting representative samples from populations (Vieira et al., 2019, 15 citations). Common methods include stratified sampling in telephone surveys (Vieira et al., 2019) and purposive sampling in multiple case studies (Teixeira and Bomfim, 2016, 23 citations). Over 10 papers from Brazilian journals highlight applications in health, business, and education fields.
Why It Matters
Accurate sampling prevents bias in empirical studies, as seen in the Educatel survey where representative sampling enabled national estimates of teacher absenteeism (Vieira et al., 2019). In autism diagnosis research, systematic review sampling identified gender-specific diagnostic challenges (Freire and Cardoso, 2022). HR management bibliometric studies used sampling to analyze publication trends, influencing resource allocation in academia (Meneses et al., 2014). Proper techniques underpin policy decisions in tourism entrepreneurship (Teixeira and Bomfim, 2016) and controllership functions (de Lira et al., 2012).
Key Research Challenges
Sample Representativeness
Achieving population representation in diverse fields like education surveys is difficult due to non-response bias (Vieira et al., 2019). Telephone sampling requires weighting adjustments for coverage errors. Studies in underrepresented groups, such as female entrepreneurs, face access limitations (Teixeira and Bomfim, 2016).
Sample Size Determination
Determining adequate sizes for case studies or bibliometric analyses balances precision and feasibility (Meneses et al., 2014). Qualitative paradigms lack standardized formulas, leading to underpowered studies. Business surveys like ERP implementations struggle with firm variability (de Lira et al., 2012).
Error Minimization
Reducing sampling and non-sampling errors in cross-sectional designs demands complex stratification (Vieira et al., 2019). Autism research highlights selection bias in gender diagnostics (Freire and Cardoso, 2022). Industrial case studies require controls for process variability (Sampaio et al., 2019).
Essential Papers
Empreendedorismo feminino e os desafios enfrentados pelas empreendedoras para conciliar os conflitos trabalho e família: estudo de casos múltiplos em agências de viagens
Rivanda Meira Teixeira, Lea Cristina Silva Bomfim · 2016 · Revista Brasileira de Pesquisa em Turismo · 23 citations
As mulheres vêm conquistando cada vez mais espaço em diversas áreas profissionais e essa evolução também ocorre no campo do empreendedorismo. No Brasil o GEM 2013 identificou que, pela primeira vez...
Diagnóstico do autismo em meninas
Milson Gomes Freire, Heloísa dos Santos Peres Cardoso · 2022 · Revista Psicopedagogia · 22 citations
O Transtorno do Espectro Autista (TEA) é um transtorno do neurodesenvolvimento, com diferentes etiologias, presente em ambos os gêneros. O objetivo desse estudo foi compreender sobre o diagnóstico ...
A produção científica Brasileira sobre a gestão de recursos humanos entre 2001 e 2010
Pedro Paulo Murce Meneses, Francisco Antônio Coelho, Rodrigo Rezende Ferreira et al. · 2014 · RAM. Revista de Administração Mackenzie · 15 citations
Em 1990, conforme revisão de literatura empreendida na área de gestão de recursos humanos, prevaleciam os estudos de caso como método de pesquisa. Desde então, a exemplo da gestão por competências,...
Desenho da amostra e participação no Estudo Educatel
Marcel de Toledo Vieira, Rafael Moreira Claro, Ada Ávila Assunção · 2019 · Cadernos de Saúde Pública · 15 citations
Resumo: O Educatel Brasil 2015/2016 foi um estudo transversal, realizado por entrevista telefônica, com o objetivo de oferecer informações a respeito da saúde e absenteísmo de professores da Educaç...
Uses of ERP Systems and Their Influence on Controllership Functions in Brazilian Companies
Arnaldo Morozini de Lira, Cláudio Parisi, Ivam Ricardo Peleias et al. · 2012 · Journal of Information Systems and Technology Management · 13 citations
Controllership and Information Technology provide ways for companies to adapt to the competitive context of business environments. As such, the aim of this research is to identify and analyze the i...
IMPLEMENTAÇÃO DE CONTROLE ESTATÍSTICO DE APERTADEIRAS EM UMA INDÚSTRIA AUTOMOTIVA: ESTUDO DE CASO
Nilo Antônio de Souza Sampaio, José Glênio Medeiros de Barros, Maria da Glória Diniz de Almeida et al. · 2019 · Revista SODEBRAS · 12 citations
Stories are reports produced by man from his gaze on situations experienced in society, writing them requires a hard and continuous work. From this perspective, to understand the History of the Con...
Competências gerenciais em ação - o caso do Banco do Brasil
Edson Bündchen, Carlos Ricardo Rossetto, Anielson Barbosa da Silva · 2011 · REAd Revista Eletrônica de Administração (Porto Alegre) · 10 citations
Este artigo teve como objetivo identificar as competências gerenciais mais importantes na percepção dos próprios gerentes quando da atuação nas agências do Banco do Brasil. A pesquisa, de caráter d...
Reading Guide
Foundational Papers
Start with Meneses et al. (2014, 15 citations) for bibliometric sampling evolution and de Lira et al. (2012, 13 citations) for business survey designs, as they establish pre-2015 baselines across fields.
Recent Advances
Study Vieira et al. (2019, 15 citations) for modern stratified sampling and Freire and Cardoso (2022, 22 citations) for systematic review techniques in health.
Core Methods
Core methods include stratified probability sampling (Vieira et al., 2019), purposive case selection (Teixeira and Bomfim, 2016), and hierarchical content analysis (Mazieri et al., 2023).
How PapersFlow Helps You Research Research Sampling Techniques
Discover & Search
Research Agent uses searchPapers and exaSearch to find sampling papers like 'Desenho da amostra e participação no Estudo Educatel' (Vieira et al., 2019), then citationGraph reveals connections to HR bibliometrics (Meneses et al., 2014) and findSimilarPapers uncovers related autism sampling (Freire and Cardoso, 2022).
Analyze & Verify
Analysis Agent applies readPaperContent to extract sampling designs from Vieira et al. (2019), verifies claims with CoVe for bias reduction, and uses runPythonAnalysis with pandas to compute sample size margins from Educatel data; GRADE grading scores methodological rigor in probability sampling.
Synthesize & Write
Synthesis Agent detects gaps in non-probability sampling across fields, flags contradictions between case study approaches (Teixeira and Bomfim, 2016 vs. Meneses et al., 2014); Writing Agent employs latexEditText for methodology sections, latexSyncCitations for 10+ papers, and latexCompile for polished reports with exportMermaid flowcharts of sampling hierarchies.
Use Cases
"Compute power analysis for 1000-teacher survey like Educatel using Vieira et al. methods."
Research Agent → searchPapers(Vieira 2019) → Analysis Agent → readPaperContent → runPythonAnalysis(pandas power calc, matplotlib plot) → researcher gets CSV of sample sizes with 95% CI.
"Write LaTeX section comparing probability vs non-probability sampling in Brazilian studies."
Synthesis Agent → gap detection(Meneses 2014, Teixeira 2016) → Writing Agent → latexEditText(draft) → latexSyncCitations(10 papers) → latexCompile → researcher gets PDF with cited sampling tables.
"Find GitHub repos analyzing IRAMUTEQ sampling from Mazieri et al. 2023."
Research Agent → searchPapers(Mazieri 2023) → Code Discovery (paperExtractUrls → paperFindGithubRepo → githubRepoInspect) → researcher gets repo code for hierarchical classification analysis.
Automated Workflows
Deep Research workflow conducts systematic reviews of 50+ sampling papers, chaining searchPapers → citationGraph → GRADE grading for structured reports on probability designs. DeepScan applies 7-step analysis with CoVe checkpoints to verify sample error claims in Vieira et al. (2019). Theorizer generates hypotheses on sampling biases from lit review of Freire and Cardoso (2022).
Frequently Asked Questions
What defines research sampling techniques?
Research sampling techniques are methods for selecting subsets from populations to ensure representativeness, including probability (random, stratified) and non-probability (purposive, case-based) designs (Vieira et al., 2019).
What are common sampling methods in these papers?
Papers use stratified telephone sampling (Vieira et al., 2019), multiple case studies (Teixeira and Bomfim, 2016), and systematic reviews (Freire and Cardoso, 2022).
Which papers are key for sampling?
Vieira et al. (2019, 15 citations) details Educatel sample design; Meneses et al. (2014, 15 citations) analyzes HR lit sampling; Teixeira and Bomfim (2016, 23 citations) applies case sampling.
What open problems exist in sampling?
Challenges include gender bias in diagnostics (Freire and Cardoso, 2022), non-response in surveys (Vieira et al., 2019), and standardization for qualitative sizes (Meneses et al., 2014).
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