adj_reps {STMr}

Family of functions to adjust number of repetition

Description

These functions are reverse version of the adj_perc_1RM family of functions. Use these when you want to estimate number of repetitions to be used when using the known %1RM and level of adjustment

Usage

adj_reps_RIR(
  perc_1RM,
  adjustment = 0,
  mfactor = 1,
  max_reps_func = max_reps_epley,
  ...
)

adj_reps_DI(
  perc_1RM,
  adjustment = 1,
  mfactor = 1,
  max_reps_func = max_reps_epley,
  ...
)

adj_reps_rel_int(
  perc_1RM,
  adjustment = 1,
  mfactor = 1,
  max_reps_func = max_reps_epley,
  ...
)

adj_reps_perc_MR(
  perc_1RM,
  adjustment = 1,
  mfactor = 1,
  max_reps_func = max_reps_epley,
  ...
)

Arguments

perc_1RM

Numeric vector. %1RM used (use 0.5 for 50%, 0.9 for 90%)

adjustment

Numeric vector. Adjustment to be implemented

mfactor

Numeric vector. Default is 1 (i.e., no adjustment). Use mfactor = 2 to generate ballistic adjustment and tables

max_reps_func

Max reps function to be used. Default is max_reps_epley

...

Forwarded to max_reps_func. Usually the parameter value. For example klin = 36 when using max_reps_linear as max_reps_func function

Value

Numeric vector. Predicted number of repetitions to be performed

Functions

• adj_reps_RIR(): Adjust number of repetitions using the Reps In Reserve (RIR) approach

• adj_reps_DI(): Adjust number of repetitions using the Deducted Intensity (DI) approach

• adj_reps_rel_int(): Adjust number of repetitions using the Relative Intensity (RelInt) approach

• adj_reps_perc_MR(): Adjust number of repetitions using the % max reps (%MR) approach

Examples

# ------------------------------------------
# Adjustment using Reps In Reserve (RIR)
adj_reps_RIR(0.75)

# Use ballistic adjustment (this implies doing half the reps)
adj_reps_RIR(0.75, mfactor = 2)

# Use 2 reps in reserve
adj_reps_RIR(0.75, adjustment = 2)

# Use Linear model
adj_reps_RIR(0.75, max_reps_func = max_reps_linear, adjustment = 2)

# Use Modifed Epley's equation with a custom parameter values
adj_reps_RIR(
  0.75,
  max_reps_func = max_reps_modified_epley,
  adjustment = 2,
  kmod = 0.06
)
# ------------------------------------------
# Adjustment using Deducted Intensity (DI)
adj_reps_DI(0.75)

# Use ballistic adjustment (this implies doing half the reps)
adj_reps_DI(0.75, mfactor = 2)

# Use 10% deducted intensity
adj_reps_DI(0.75, adjustment = -0.1)

# Use Linear model
adj_reps_DI(0.75, max_reps_func = max_reps_linear, adjustment = -0.1)

# Use Modifed Epley's equation with a custom parameter values
adj_reps_DI(
  0.75,
  max_reps_func = max_reps_modified_epley,
  adjustment = -0.1,
  kmod = 0.06
)
# ------------------------------------------
# Adjustment using Relative Intensity (RelInt)
adj_reps_rel_int(0.75)

# Use ballistic adjustment (this implies doing half the reps)
adj_reps_rel_int(0.75, mfactor = 2)

# Use 85% relative intensity
adj_reps_rel_int(0.75, adjustment = 0.85)

# Use Linear model
adj_reps_rel_int(0.75, max_reps_func = max_reps_linear, adjustment = 0.85)

# Use Modifed Epley's equation with a custom parameter values
adj_reps_rel_int(
  0.75,
  max_reps_func = max_reps_modified_epley,
  adjustment = 0.85,
  kmod = 0.06
)
# ------------------------------------------
# Adjustment using % max reps (%MR)
adj_reps_perc_MR(0.75)

# Use ballistic adjustment (this implies doing half the reps)
adj_reps_perc_MR(0.75, mfactor = 2)

# Use 85% of max reps
adj_reps_perc_MR(0.75, adjustment = 0.85)

# Use Linear model
adj_reps_perc_MR(0.75, max_reps_func = max_reps_linear, adjustment = 0.85)

# Use Modifed Epley's equation with a custom parameter values
adj_reps_perc_MR(
  0.75,
  max_reps_func = max_reps_modified_epley,
  adjustment = 0.85,
  kmod = 0.06
)