Sign-up now for individual statistics consulting

CRASE is offering one-on-one statistical consulting. Come with questions about a new study, an existing data set, analytic techniques, or writing up your data. Lauren Howe is a postdoctoral scholar in psychology at Stanford University and adjunct faculty at USF in psychology. She is a social psychologist who uses a variety of statistical tools in her research and has extensive experience teaching statistics and offering statistical consultation using a variety of analytic techniques.

Please only register for one appointment per day. Appointments must be made at least 24 hours in advance.  Lauren will meet during these times via Zoom.

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Dates available:
Tuesday January 23 9 a.m. – 12 p.m.
Thursday January 25 1:30 p.m. – 4:30 p.m.
Monday January 29 9 a.m. – 12 p.m.
Tuesday January 31 1 p.m.– 3 p.m.
Tuesday February 6 9 a.m. – 12 p.m.
Thursday February 8 2 p.m. – 4 p.m.
Monday February 12 9 a.m. – 12 p.m.
Tuesday February 13 9 a.m. – 12 p.m.

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After you make your appointment, Lauren will contact you with the Zoom meeting invitation.

Services Offered

Statistical Software

  • Linguistic Inquiry and Word Count text analysis software
  • R Statistical Software
    • Packages:
      • ggplot2 (plotting)
      • reshape2 (restructuring datasets)
      • psych (alpha, ICC, partial correlations, creating scales)
      • lme4 (mixed-effects models)
      • mediation (causal mediation analysis)
      • lavaan (multiple mediation, moderated mediation, structural equation modeling)
      • factanal (factor analysis)

Statistical Methodologies

  • Plotting in R using package ggplot2 and R basics
  • Transforming variables
  • Creating scales from multiple variables
  • Cleaning datasets
  • Merging and restructuring datasets
  • Creating pivot tables
  • T-tests (paired, independent groups)
  • Correlation, partial correlation
  • Linear regression, logistic regression, multiple regression
  • Mixed-effects models
  • Mediation, multiple mediation, moderated mediation
  • Structural equation modeling
  • Factor analysis