Statistical Analysis and Measurement Consultants, Inc. has experience using many different statistical methods. Our approach is to get a clear understanding of your research questions and select an appropriate statistical method to answer your hypotheses. Following are some of the statistical methods we have applied to such fields as business productivity, grant funded research, marketing research, and academic research.
S.A.M.C., Inc. has helped clients interpret the results from independent and dependent samples t-tests, one way ANOVA, analysis of variance (ANOVA), analysis of covariance (ANCOVA), multivariate analysis of variance (MANOVA), repeated measures analysis of variance, linear mixed models analysis.
We have assisted researchers with Pearson correlation, point biserial correlation, partial correlation, Spearman rank correlation, Kendall's tau, simple linear regression, multiple regression (hierarchical, stepwise, with or without the use of blocking variables), ordinal regression, binomial logistic regression, multinomial logistic regression.
S.A.M.C., Inc. has provided consultation with advanced multivariate methods including canonical correlation, structural equation modeling, path analysis, confirmatory factor analysis, common factor analysis, principal components analysis, discriminant function analysis, hierarchical cluster analysis, model selection loglinear analysis, general loglinear analysis, and logit loglinear analysis.
We help clients understand relatively simple output (means, standard deviations, odds, odds ratios) as well as more advanced tests (Wilk's Lambda, F tests, Greenhouse-Geisser, Mauchly, Bartlett, etc.) depending on the task.
We have helped clients understand Phi, Cramer's V, Kruskal Wallis, Komolgov Smirnoff, eta, analysis of contingency tables, Kolmogorov-Smirnov, Wilcoxon, binomial, crosstabs, chi-square, Mann-Whitney U, Moses extreme reactions, Wald-Wolfowitz runs, sign test, McNemars test, Friedmans test, Kendall's W, Cochran's Q, reliability analysis (including Cronbach's alpha, split half, etc.).
S.A.M.C., Inc. can use our extensive graphing capability to help clients present results using bar, line, and pie charts, ordinary frequency distributions, boxplots, error bar charts, scatterplots, histograms (with or without the normal curve), normal probability plots (P-P or Q-Q), and detrended normal probability plots.
In the field of medical research, we have experience with ROC curves to estimate sensitivity and specificity. In addition, we can run survival type analyses including Life tables, Kaplan-Meier curves, and cox regression.
Regardless of the field of research, we take pride in our ability to explain the output to researchers who may not have a strong quantitative background, all for a reasonable fee.
