Table of Means

Table of Means

Purpose

The table of means presents the average score for each product and attribute in sensory analysis and each product and consumer rating (liking, JAR or CATA) in consumer analysis. The means are averaged across assessor, sessions and replicates. These means can be used to begin to explore the data and understand how products differ.

Data Format

  1. Profiling.xlsx
  2. Consumer.xlsx

For EyeOpenR to read your data, the first five columns of the ‘Data’ sheet must be in the following order: assessor (consumer), product, session, replicate and order (sequence). For sensory analysis the data for attributes should be in the sixth column (column F) onwards. There should be one column for each attribute. The attributes data should be numeric. For consumer analysis the data for consumer liking and other consumer assessments (ratings) should be in the sixth column (column F) onwards. There should be one column for each rating. These are described as attributes in the options.

If there is no session, replicate or order information then these columns should contain the value ‘1’ in each cell.

Additional information about the data in the ‘Data’ sheet can be included in additional sheets. The ‘Attributes’ sheet can be used to specify the names of the attributes, data types and minimum and maximum values that are used to check data quality. The ‘Assessors’ sheet can be used to specify assessor names if codes are used in the ‘Data’ sheet. Similarly, the ‘Products’ sheet can be used to specify product names if codes are used in the ‘Data’ sheet. See the example spreadsheet for an illustration of the data format. 

Background

It can be helpful when first looking at sensory and consumer data to explore the means averaged across assessor, sessions and replicates. This gets to the information that is of most interest, ie how products differ from each other.

There is also the ability to look at this data one assessor at a time, or one session at a time or one replicate at a time. This can be useful to get a better understanding of the data.

This module does not test whether differences between products are statistically significant. Use other modules such as ‘ANOVA for multiple comparison tests’ to do this.

Options

  1. Split results on: There are five options here; None, Judge, Attribute, Product, Session. If a choice is made other than None, the results are presented separately for each level of the split selected. For consumer studies ‘Attribute’ refers to the consumer ratings. Note that if a split is selected, and the Type of Mean selected is ‘Adjusted’ then EyeOpenR compares the chosen model with the split option and if it is not possible to calculate adjusted means this option will be ignored and a message written into the ‘Information’ tab of the results.
  2. Treat Sessions/Replicates Separately: There are three options; ‘No’, ‘Sessions’, ‘Replicates’. Only one option can be selected. If either sessions or replicates is selected then each results table shows results for each attribute split by either session or replicate.
  3. Type of Mean: There are two options: ‘Adjusted’ presents adjusted means derived from an ANOVA specified using the four options that follow. ‘Arithmetic’ presents unadjusted means and if selected the next four options are greyed out because they are not needed. If the design of the study is balanced then adjusted and arithmetic means are identical. If the model selected is not compatible with choices made for the Split results by or Treat Sessions/Replicates Separately options then the arithmetic means are calculated and note is written to the ‘Information’ tab of the results.
  4. Assessor Effect: Only available if ‘Adjusted’ means have been selected. Includes assessor effects in the ANOVA and therefore means are adjusted for assessor differences.
  5. Session Effect: Only available if ‘Adjusted’ means have been selected. Includes session effects in the ANOVA and therefore means are adjusted for assessor differences.
  6. Replicate Effect: Only available if ‘Adjusted’ means have been selected. Includes replicate effects in the ANOVA and therefore means are adjusted for assessor differences.
  7. Interaction: Only available if ‘Adjusted’ means have been selected. If at least one of the preceding three effects has been selected, the two-way interaction of product and those effects is also included in the ANOVA. If no other effect has been selected, the ANOVA is a 1 way ANOVA with product and this option is ignored.
  8. Number of Decimals for Values: Specify the number of decimal places shown for means.

Results and Interpretation

  1. Means: This shows a table with products in the columns and attributes in the rows. The table includes the means (or adjusted means depending on the option selected for the ‘Type of Mean’). If the ‘Split results on’ option was anything other than ‘None’ there is a table for each of the split levels. These are selected at the very top of the page. If the ‘Treat Sessions/Replicates Separately’ option has been selected then each table has additional rows,  one for each level of attribute and either session or replicate. The more granular the data the fewer the number of observations in the means. The tables are presented with the products in the columns so that you can compare products for each attribute by looking at the values in each row.
  2. Information: This shows any notes or warnings that are relevant to the procedure. If the adjusted means have been selected a description of the ANOVA model is included here.

Technical Information

R packages used:

  1. averagetable (SensoMineR) for calculating the means. 

Reference

  1. Martin Bland (2015) “An Introduction to Medical Statistics – 4th Edition”, Oxford University Press.  See chapter 4 “Summarizing data”.



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