Does anyone knows how to evaluate ceiling effect?

Posted on: May 15, 2018, by :

How can we assess the ceiling effect or floor effect of a questionnaire?

You could also use item response theory if you have scales of Likert items, even if they have floor/ceiling effects. In most instances, scores have a less severe floor or ceiling effect than individual items.

I am perfomring linear regression analysis in SPSS , and my dependant variable is not-normally distrubuted. Could anyone help me if the results…

British Journal of Mathematical and Statistical Psychology

First, you can look whether your data are skewed depending on the skew (positive vs. negative), you can then use different kinds of transformations to correct for skewness (e.g. log transformation). If this does not work, you may want to try nonparametric tests (e.g., bootstrapping).

Further statistical study, and scientific judgment, can resolve whether or not the observations are due to a ceiling or are the truth of the matter.

Is linear regression valid when the outcome (dependant variable) not normally distributed?

How does the floor or ceiling effect in the questionnaire reduces the responsiveness?

In cognitive psychology, the measurement of the time to respond to a given stimulus is often of interest. In these measurements, a ceiling may be the lowest possible number ie., the fewest milliseconds to a response, rather than the highest value, as is the usual interpretation of ceiling.

I performed a multiple linear regression analysis with 1 continuous and 8 dummy variables as predictors. The analysis revealed 2 dummy variables…

Does anyone knows how to evaluate ceiling effect?

A completely different traditional approach would be to apply a transformation like square root, log, or inverse to try to make the data more normal.

The theory behind the floor or ceiling effect reducing the responsiveness of questionnaire !

British Journal of Mathematical and Statistical Psychology

I use an online calculator for between subjects t-tests, as my version of SPSS doesnt seem to offer effect sizes. I recollect checking what it…

In one of my measurement CFA models (using AMOS) the factor loading of two items are smaller than 0.3. I found some scholars that mentioned only…

A SPECIFICATION TEST FOR NORMALITY ASSUMPTION FOR THE TRUNCATED AND CENSORED TOBIT MODELS

What is the minimum acceptable item-total correlation in a multi-dimensional questionnaire?

If the floor or ceiling effects cause your data to become dichotomous (or can easily be collapsed into two categories without much loss of information) and you want to predict that variable, then logistic regression would be appropriate.

3.  Vogt, W. Paul (2005). Dictionary of Statistics & Methodology: A Nontechnical Guide for the Social Sciences (Third ed.). SAGE. p. 40 (entry ceiling effect).

How can I calculate the effect-size for a repeated measures t-test?

In linguistic validation of some multi-dimensional questionnaires for our population (with 26 to 34 items and about 5 sub-scales), we encountered…

It is desirable that for the normal distribution of data the values of skewness should be near to 0. What if the values are +/- 3 or above?

Floor and Ceiling of SF-36, how can I measure it?

Tobit analysis is designed to estimate a regression model with data censored by floor or ceiling effects that might be useful to you. I found this presentation helpful:

A note on the use of the Tobit approach for tests scores with floor or ceiling effects

Muthn (1989) developed the Tobit approach to deal with censored variables in structural equation modelling. We performed a simulation study to evaluate the effectiveness of this approach for the type of censoring that occurs for sums of Likert items. Results indicated that estimated correlations and factor loadings were substantially biased downwards, and that goodness-of-fit tests were inaccurate. Furthermore, the magnitude of distortion depended on characteristics of the scales such as the amount of censoring, scale length, the number of response categories of the items, and the size of the correlation. When we adjusted the Tobit approach by assuming that all scores at the lower end of the scale were affected by censoring and not just the lowest score, results improved considerably. In addition, this adjusted Tobit approach was superior to alternative procedures that deal with censoring and was easy to implement using the existing software.

1) Because I am a novice when it comes to reporting the results of a linear mixed models analysis, how do I report the fixed effect, including…

What is the acceptable range of skewness and kurtosis for normal distribution of data?

How do I report the results of a linear mixed models analysis?

How to calculate the effect size in multiple linear regression analysis?

1.  Kaufman, Alan S. (2009). IQ Testing 101. New York: Springer Publishing. pp. 151153.

Amrita Institute of Medical Sciences and Research Centre

Tetrachoric correlations are estimated Pearson correlations estimated from dichotomous data. If you dichotomized your data by coding your most extreme response versus the others, then a matrix of tetrachoric correlations would produce better outcomes for covariance models, including factor analysis, structural equations modeling, and regression.

Does anyone knows how to assess ceiling or floor effect in non-longitudinal surveys? Is the tobit model the most appropriate for likert -type measures? Can I use SPSS for doing the ceililng effect analysis?

2.  Po, Alain Li Wan (1998). Dictionary of Evidence-based Medicine. Radcliffe Publishing. p. 20.

Does anyone knows how to evaluate ceiling effect?

I used SF-36 in my cross-sectional study, this is the first time I used it in the population where I recruited my sample. So, I would like to know…

Thank you all for your helpful comments!

Referees usually asks about the existence of ceiling effect or floor effect in the process of instrument development. I am interested to find the…

In response time studies, it may appear that a ceiling had occurred in the measurements due to an apparent clustering around some minimum amount of time.  Such as the 250 ms needed by many people to press a key. However, this clustering could actually represent a natural physiological limit of response time, rather than an artifact of the stopwatch sensitivity (which of course would be a ceiling effect).

Amrita Institute of Medical Sciences and Research Centre

What is the acceptable range for factor loading in SEM?

I hope this help; I am unsure what you are asking.  To assess a floor or ceiling effect, I would use standard descriptive methods such as box plots, numerical skew, etc. Those are certainly available in SPSS.

Does IRT provide specific analysis for ceiling/ floor effects? (As far as I recall It provides different type of information about my items, but I dont know whether is helpfull in this case).

Etude du modele tobit avec processus autoregressif.

The data are positively skewed and unfortunately this may be due to the topic of questionnaire, which is about ethics.  Responses are given on likert type scale from 1-6. If I correct the skeweness, wouldnt  I lose data? I dont know if I can dichotomize my data, but wouldnt  I lose info again?

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