This DATASETNAMEreadme.txt file was generated on 20220729 by Claudia Zuber
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GENERAL INFORMATION
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1. Title of dataset:
	AMBIS-T self-report and coach-rating

2. Contributor information: 

      Name: Claudia Zuber
      Role/Function: PI
      Institution: University of Bern
      Address: Bremgartenstrasse 145, 3012 Bern
      Email: claudia.zuber@unibe.ch
      
3. Date of data collection: 
 	Data was collected in 2018 and 2020 (performance criterion)

4. Geographic location of data collection:
	Switzerland

5. Information about funding sources that supported the collection of the data:
      Funding agency name: FOSPO (Federal Office for Sport, Magglingen) and Swiss Olympic
      


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SHARING/ACCESS INFORMATION
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1. Licenses/restrictions placed on the data:
	Access is to be asked at the contributor

2. Links to publications that cite or use the data: 
	not published yet

3. Links to other publicly accessible locations of the data: 

4. Links/relationships to additional data sets: 

5. Was data derived from another source? 
	no 


6. Recommended citation for this dataset: 

Zuber, C. (2022). AMBIS-T self-report and coach-rating
[Data set]. https://doi.org/10.48620/72


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METHODOLOGICAL INFORMATION
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**Links to publications will follow**

1. Description of methods used for collection/generation of data: 

2. Methods for processing the data: 

3. Instrument- or software-specific information needed to interpret the data:

4. Standards and calibration information:

5. Environmental/experimental conditions:

6. Describe any quality-assurance procedures performed on the data:

7. People involved with sample collection, processing, analysis and/or submission:
	Claudia Zuber, Bryan Charbonnet and Achim Conzelmann

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DATA-SPECIFIC INFORMATION FOR: [FILENAME]
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<If your data contain variables, codes or abbreviations (e.g., tabular data) you may need to explain 
them. For example, describe the number of variables and cases/rows, create a list of all your variables 
with variable name, description of the variable and labels value.
Create sections for each dataset (or file if appropriate) included>

1. Number of variables:
	17

2. Number of cases/rows:
	250

3. Variable List <with variable name, description of the variable and value labels if appropriate>

ID_athlete		ID athlete
ID_coach		ID coach
sex			sex
age			age
sport			main sport
experience		How many years of experience do you have in your sport?
performance_level_t1	level of performance at the first measurement point
performance_Level_2020	level of performance in summer 2020
Proactivity		coach-rating: scale proactivity
Ambition		coach-rating: scale ambition
Commitment		coach-rating: scale commitment
competitiveness		self-report: scale competitiveness
self_optimization	self-report: scale self-optimization
self_determination	self-report: self-determination
PRE_coach_rating	predicted likelihood for professional performance level coach-ratings
PRE_self_report		predicted likelihood for professional performance level  self-report
PRE_combination		predicted likelihood for professional performance level combination coach-rating and self-report




4. Missing data codes: 
	none

5. Specialized formats of other abbreviations used